Current image decoding and encoding methods, computer-readable invariant means, and data transmission methods.

Abstract

The invention relates to a method for decoding a current image comprising the following steps: capturing a bit stream containing the current image; dividing the encoded block in the current image to obtain one or more sub-blocks; obtaining the inverse quantization coefficients of the first sub-block; reconstructing the residual signal of the first sub-block; reconstructing the encoded block; and performing inverse quantization on the first sub-block. The invention also relates to a method for encoding a current image comprising the following steps: dividing the encoded block in the current image to obtain one or more sub-blocks; obtaining the coefficients of the first sub-block; obtaining the quantization transformation coefficients of the first sub-block; and generating a bit stream by encoding the quantization transformation coefficients of the first sub-block. Furthermore, the invention relates to a computer-readable invariant medium for storing data associated with the image signal and a method for transmitting data associated with the image signal.

Description

Video data encoding / decoding method and device The present invention relates to video data encoding and decoding technology, and more specifically, to a method and device for processing encoding and decoding of 360-degree video for realistic media services. With the spread of the Internet and mobile devices and the development of information and communication technology, the use of multimedia data is rapidly increasing. Recently, the demand for high-resolution and high-quality images such as HD (High Definition) images and UHD (Ultra High Definition) images has been occurring in various fields, and the demand for realistic media services such as virtual reality and augmented reality is rapidly increasing. In particular, in the case of 360-degree images for virtual reality and augmented reality, the amount of data generated increases significantly because multi-view images captured by multiple cameras are processed, but the performance of the image processing system to process this is insufficient. In this way, in conventional image encoding / decoding methods and devices, performance improvement in image processing, especially image encoding / decoding, is required. The purpose of the present invention to solve the above-mentioned problems is to provide a method for improving the image setting process in the initial stages of encoding and decoding. More specifically, the purpose is to provide an encoding and decoding method and device for improving the image setting process considering 360-degree image characteristics. One aspect of the present invention to achieve the above object provides a method for decoding a 360-degree video. Here, a method for decoding a 360-degree video may include a step of receiving a bitstream in which a 360-degree video is encoded, a step of generating a predicted video by referring to syntax information obtained from the received bitstream, a step of obtaining a decoded video by combining the generated predicted video with a residual video obtained by inversely quantizing and inversely transforming the bitstream, and a step of reconstructing the decoded video into a 360-degree video according to a projection format. Here, the syntax information may include projection format information for the 360-degree image. Here, the projection format information may be information indicating at least one of an ERP (Equi-Rectangular Projection) format that projects the 360-degree image onto a two-dimensional plane, a CMP (CubeMap Projection) format that projects the 360-degree image onto a cube, an OHP (OctaHedron Projection) format that projects the 360-degree image onto an octahedron, and an ISP (IcoSahedral Projection) format that projects the 360-degree image onto a polyhedron. Here, the reconstructing step may include a step of obtaining arrangement information according to regional packing by referring to the syntax information, and a step of rearranging each block of the decoded image according to the arrangement information. Here, the step of generating the predicted image may include a step of performing image expansion on a reference picture obtained by restoring the bitstream, and a step of generating the predicted image by referring to the reference picture on which the image expansion has been performed. Here, the step of performing the image expansion may include a step of performing image expansion based on the segmentation unit of the reference image. In this case, the step of performing image expansion based on the above-mentioned division unit can generate an individually expanded area for each division unit by using the boundary pixels of the division unit. Here, the extended region can be generated by using boundary pixels of a segmentation unit that is spatially adjacent to the segmentation unit to be expanded or boundary pixels of a segmentation unit that has image continuity with the segmentation unit to be expanded. In this case, the step of performing image expansion based on the above-mentioned segmentation unit can generate an expanded image for the combined area by using boundary pixels of an area in which two or more spatially adjacent segmentation units are combined among the above-mentioned segmentation units. In this case, the step of performing image expansion based on the above-mentioned division units can generate an expanded area between the adjacent division units by using all adjacent pixel information of spatially adjacent division units among the above-mentioned division units. In this case, the step of performing image expansion based on the above-described segmentation unit can generate the expanded area by using the average value of adjacent pixels of each of the above-described spatially adjacent segmentation units. Here, the step of generating the predicted image may include a step of obtaining a motion vector candidate group including motion vectors of blocks adjacent to the current block to be decoded from motion information included in the syntax information, a step of deriving a predicted motion vector from the motion vector candidate group based on selection information extracted from the motion information, and a step of determining a predicted block of the current block to be decoded using a final motion vector derived by adding the predicted motion vector to a differential motion vector extracted from the motion information. Here, the motion vector candidate group may be composed of only motion vectors for blocks belonging to a surface that has image continuity with the surface to which the current block belongs, among the adjacent blocks, if the blocks adjacent to the current block are different from the surface to which the current block belongs. Here, the adjacent block may mean a block adjacent in at least one direction among the upper left, upper right, left, and lower left of the current block. Here, the final motion vector may indicate a reference area set in an area that belongs to at least one reference picture based on the current block and has image continuity between surfaces according to the projection format. Here, the reference picture may be expanded based on the image continuity according to the projection format in the up, down, left, and right directions, and then the reference area may be set. Here, the reference picture is extended to the surface unit, and the reference area can be set across the surface boundary. Here, the motion information may include at least one of a reference picture list to which the reference picture belongs, an index of the reference picture, and a motion vector indicating the reference area. Here, the step of generating a prediction block of the current block may include the step of dividing the current block into a plurality of sub-blocks and generating a prediction block for each of the plurality of divided sub-blocks. When using the image encoding / decoding method and device according to the embodiment of the present invention as described above, compression performance can be improved. In particular, compression performance can be improved for 360-degree images. FIG. 1 is a block diagram of an image encoding device according to one embodiment of the present invention. FIG. 2 is a block diagram of an image decoding device according to one embodiment of the present invention. Figure 3 is an example of dividing image information into layers to compress the image. FIG. 4 is a conceptual diagram illustrating several examples of image segmentation according to one embodiment of the present invention. FIG. 5 is another example of an image segmentation method according to one embodiment of the present invention. Figure 6 is an example of a general image resizing method. FIG. 7 is an example diagram for image resizing according to one embodiment of the present invention. FIG. 8 is an exemplary diagram of a method for configuring an expanded area in an image resizing method according to one embodiment of the present invention. FIG. 9 is an exemplary diagram of a method for configuring a deleted area and a reduced area in an image size adjustment method according to one embodiment of the present invention. Figure 10 is an example diagram for image reconstruction according to one embodiment of the present invention. Figure 11 is an exemplary diagram showing images before and after an image setting process according to one embodiment of the present invention. FIG. 12 is an example diagram of size adjustment for each segmentation unit in an image according to one embodiment of the present invention. Figure 13 is an example diagram for a set of resizing or setting of segmentation units within an image. Figure 14 is an example diagram showing the process of resizing an image and the process of resizing a segmentation unit within an image. Figure 15 is an example diagram showing a three-dimensional space representing a three-dimensional image and a two-dimensional plane space. FIGS. 16A to 16D are conceptual diagrams for explaining a projection format according to one embodiment of the present invention. Figure 17 is a conceptual diagram illustrating an implementation of a projection format according to one embodiment of the present invention as included within a rectangular image. FIG. 18 is a conceptual diagram of a method for converting a projection format into a rectangular shape according to one embodiment of the present invention, wherein a surface is rearranged to exclude meaningless areas. FIG. 19 is a conceptual diagram showing a regional packaging process performed on a rectangular image using a CMP projection format according to one embodiment of the present invention. Figure 20 is a conceptual diagram for 360-degree image segmentation according to one embodiment of the present invention. FIG. 21 is an example of 360-degree image segmentation and image reconstruction according to an embodiment of the present invention. Figure 22 is an example of dividing an image projected by CMP or a packaged image into tiles. FIG. 23 is a conceptual diagram illustrating an example of resizing a 360-degree image according to one embodiment of the present invention. FIG. 24 is a conceptual diagram for explaining continuity between surfaces in a projection format (e.g., CMP, OHP, ISP) according to one embodiment of the present invention. Figure 25 is a conceptual diagram for explaining the continuity of the surface of Figure 21c, which is an image obtained through an image reconstruction process or a regional packaging process in a CMP projection format. FIG. 26 is an exemplary diagram for explaining image resizing in a CMP projection format according to one embodiment of the present invention. FIG. 27 is an exemplary diagram illustrating resizing of a packaged image converted to a CMP projection format according to one embodiment of the present invention. FIG. 28 is an exemplary diagram for explaining a data processing method in resizing a 360-degree image according to one embodiment of the present invention. Figure 29 is an example diagram showing a tree-based block form. Figure 30 is an example diagram showing a type-based block form. Figure 31 is an exemplary diagram showing various block shapes that can be obtained from the block division unit of the present invention. FIG. 32 is an exemplary diagram for explaining tree-based segmentation according to one embodiment of the present invention. FIG. 33 is an exemplary diagram for explaining tree-based segmentation according to one embodiment of the present invention. Figure 34 is an example diagram showing various cases of obtaining a prediction block through inter-screen prediction. FIG. 35 is an example diagram for configuring a reference picture list according to one embodiment of the present invention. Figure 36 is a conceptual diagram illustrating a movement model other than movement according to one embodiment of the present invention. FIG. 37 is an exemplary diagram showing motion estimation in sub-block units according to one embodiment of the present invention. FIG. 38 is an exemplary diagram showing a block referenced for predicting motion information of a current block according to one embodiment of the present invention. FIG. 39 is an exemplary diagram showing a block referenced for predicting motion information of a current block in a motion model other than a moving one according to one embodiment of the present invention. FIG. 40 is an example diagram for performing inter-screen prediction using an extended picture according to one embodiment of the present invention. Figure 41 is a conceptual diagram showing the expansion of a surface unit according to one embodiment of the present invention. FIG. 42 is an example diagram of performing inter-screen prediction using an extended image according to one embodiment of the present invention. FIG. 43 is an example diagram for performing inter-screen prediction using an extended reference picture according to one embodiment of the present invention. FIG. 44 is an exemplary diagram of a configuration of a candidate group for motion information prediction of inter-screen prediction in a 360-degree video according to one embodiment of the present invention. The present invention can have various modifications and various embodiments, and specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to specific embodiments, but should be understood to include all modifications, equivalents, or substitutes included in the spirit and technical scope of the present invention. The terms first, second, A, B, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are only used to distinguish one component from another. For example, without departing from the scope of the present invention, the first component may be referred to as the second component, and similarly, the second component may also be referred to as the first component. The term and / or includes any combination of a plurality of related described items or any item among a plurality of related described items. When it is said that a component is "connected" or "connected" to another component, it should be understood that it may be directly connected or connected to that other component, but that there may be other components in between. On the other hand, when it is said that a component is "directly connected" or "directly connected" to another component, it should be understood that there are no other components in between. The terminology used in this application is only used to describe specific embodiments and is not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly indicates otherwise. In this application, it should be understood that the terms "comprises" or "has" and the like are intended to specify the presence of a feature, number, step, operation, component, part or combination thereof described in the specification, but do not exclude in advance the possibility of the presence or addition of one or more other features, numbers, steps, operations, components, parts or combinations thereof. Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms defined in commonly used dictionaries, such as those defined in common dictionaries, should be interpreted as having a meaning consistent with the contextual meaning they have in the relevant art, and shall not be interpreted in an idealized or overly formal sense, unless expressly defined in this application. The video encoding device and the video decoding device may be user terminals such as a personal computer (PC), a notebook computer, a personal digital assistant (PDA), a portable multimedia player (PMP), a PlayStation Portable (PSP), a wireless communication terminal, a smart phone, a TV, a virtual reality device (VR), an augmented reality device (AR), a mixed reality device (MR), a head mounted display (HMD), smart glasses, etc., or server terminals such as an application server and a service server, and may include various devices including a communication device such as a communication modem for performing communication with various devices or wired / wireless communication networks, a memory for storing various programs and data for encoding or decoding images or for predicting within a screen or between screens for encoding or decoding, and a processor for executing a program to perform calculations and controls. In addition, an image encoded into a bitstream by an image encoding device can be transmitted to an image decoding device through a wired or wireless communication network (Network) such as the Internet, a local area network, a wireless LAN, a WiBro network, a mobile communication network, etc. in real time or non-real time, or through various communication interfaces such as a cable or a universal serial bus (USB), and can be decoded by the image decoding device, restored into an image, and played back. Additionally, an image encoded into a bitstream by an image encoding device may be transmitted from the encoding device to the decoding device via a computer-readable recording medium. The above-mentioned video encoding device and video decoding device may be separate devices, but may be made into a single video encoding / decoding device depending on the implementation. In that case, some components of the video encoding device may be implemented to include at least the same structure as some components of the video decoding device as substantially the same technical elements or to perform at least the same function. Therefore, in the detailed description of the technical elements and their operating principles below, redundant descriptions of the corresponding technical elements will be omitted. And since the image decoding device corresponds to a computing device that applies the image encoding method performed in the image encoding device to decoding, the following description will focus on the image encoding device. A computing device may include a memory storing a program or software module implementing an image encoding method and / or an image decoding method, and a processor connected to the memory to execute the program. In addition, the image encoding device may be referred to as an encoder, and the image decoding device may be referred to as a decoder, respectively. Typically, an image can be composed of a series of still images, and these still images can be divided into GOP (Group of Pictures) units, and each still image can be referred to as a picture. At this time, the picture can represent one of a frame or a field in a progressive signal or an interlace signal, and when encoding / decoding is performed in frame units, the image can be represented as a 'frame', and when performed in field units, the image can be represented as a 'field'. The present invention is described assuming a progressive signal, but it can also be applied to an interlace signal. As upper concepts, there can be units such as GOP and sequence, and furthermore, each picture can be divided into predetermined areas such as slices, tiles, and blocks. Further, one GOP can include units such as I picture, P picture, and B picture. An I picture may refer to a picture that is encoded / decoded on its own without using a reference picture, and a P picture and a B picture may refer to a picture that is encoded / decoded by performing processes such as motion estimation and motion compensation using a reference picture. In general, for a P picture, an I picture and a P picture can be used as reference pictures, and for a B picture, an I picture and a P picture can be used as reference pictures, but this definition above may also change depending on the encoding / decoding settings. Here, a picture referred to for encoding / decoding is called a reference picture, and a block or pixel being referenced is called a reference block or reference pixel. In addition, the referenced data may be not only a pixel value in the spatial domain but also a coefficient value in the frequency domain, and various encoding / decoding information generated and determined during the encoding / decoding process. For example, the reference data may include prediction-related information or motion-related information within a screen in a prediction unit, transformation-related information in a transformation unit / inverse transformation unit, quantization-related information in a quantization unit / inverse quantization unit, encoding / decoding-related information (context information) in an encoding unit / decoding unit, and filter-related information in an in-loop filter unit. The minimum unit that constitutes an image can be a pixel, and the number of bits used to express one pixel is called bit depth. Generally, the bit depth can be 8 bits, and a higher bit depth can be supported depending on the encoding setting. The bit depth can support at least one bit depth depending on the color space. In addition, it can be composed of at least one color space depending on the color format of the image. Depending on the color format, it can be composed of one or more pictures having a certain size or one or more pictures having different sizes. For example, in the case of YCbCr 4:2:0, it can be composed of one luminance component (Y in this example) and two chrominance components (Cb / Cr in this example), and in this case, the composition ratio of the chrominance component and the luminance component can have a horizontal and vertical ratio of 1:2. As another example, in the case of 4:4:4, it can have the same composition ratio for the horizontal and vertical. When a picture is composed of one or more color spaces as in the above example, division into each color space can be performed. In the present invention, the description will be made based on some color spaces (Y in this example) of some color formats (YCbCr in this example), and the same or similar application (settings dependent on a specific color space) can be made to other color spaces (Cb, Cr in this example) according to the color format. However, it may also be possible to have partial differences (settings independent on a specific color space) for each color space. That is, the settings dependent on each color space can mean having settings proportional to or dependent on the composition ratio of each component (for example, determined according to 4:2:0, 4:2:2, 4:4:4, etc.), and the independent settings for each color space can mean having settings only for the corresponding color space regardless of or independently of the composition ratio of each component. In the present invention, some components can have independent settings or dependent settings depending on the encoder / decoder. The configuration information or syntax elements required in the video encoding process can be determined at the unit level of video, sequence, picture, slice, tile, block, etc., and can be included in the bitstream and transmitted to the decoder as units such as VPS (Video Parameter Set), SPS (Sequence Parameter Set), PPS (Picture Parameter Set), Slice Header, Tile Header, and Block Header, and the decoder can parse the configuration information transmitted from the encoder at the same level to use it in the video decoding process. In addition, related information can be transmitted as a bitstream in the form of SEI (Supplement Enhancement Information) or metadata and can be parsed and used. Each parameter set has a unique ID value, and a lower parameter set can have an ID value of an upper parameter set to be referenced. For example, a lower parameter set can reference information of an upper parameter set having a matching ID value among one or more upper parameter sets. Among the various examples of units mentioned above, if one unit contains one or more other units, the corresponding unit can be called a parent unit, and the contained units can be called child units. In the case of setting information occurring in the above unit, it may include content about independent settings for each unit, or content about settings that are dependent on previous, subsequent, or upper units. Here, the dependent setting may be understood as indicating the setting information of the unit with flag information that follows the settings of the previous, subsequent, or upper units (for example, a 1-bit flag, 1 if followed, 0 if not followed). The setting information in the present invention will be explained focusing on examples of independent settings, but examples of addition or replacement with content about a dependent relationship on setting information of previous, subsequent units or upper units of the current unit may also be included. Fig. 1 is a block diagram of an image encoding device according to an embodiment of the present invention. Fig. 2 is a block diagram of an image decoding device according to an embodiment of the present invention. Referring to FIG. 1, the image encoding device may be configured to include a prediction unit, a subtraction unit, a transformation unit, a quantization unit, an inverse quantization unit, an inverse transformation unit, an addition unit, an in-loop filter unit, a memory, and / or an encoding unit. Some of the above configurations may not necessarily be included, and some or all of them may be selectively included depending on the implementation, and some additional configurations not shown may be included. Referring to FIG. 2, the image decoding device may be configured to include a decoding unit, a prediction unit, an inverse quantization unit, an inverse transformation unit, an adding unit, an in-loop filter unit, and / or a memory. Some of the above configurations may not necessarily be included, and some or all of them may be selectively included depending on the implementation, and some additional configurations not shown may be included. The video encoding device and the video decoding device may be separate devices, but may be made into a single video encoding / decoding device depending on the implementation. In that case, some components of the video encoding device may be implemented to have at least the same structure or perform at least the same function as some components of the video decoding device as substantially the same technical elements. Therefore, in the detailed description of the technical elements and their operating principles below, overlapping descriptions of corresponding technical elements will be omitted. Since the video decoding device corresponds to a computing device that applies the video encoding method performed in the video encoding device to decoding, the description below will focus on the video encoding device. The video encoding device may be referred to as an encoder, and the video decoding device may be referred to as a decoder, respectively. The prediction unit can be implemented using a prediction module, which is a software module, and can generate a prediction block for a block to be encoded using an intra-prediction method or an inter-prediction method. The prediction unit predicts a current block to be encoded in an image to generate a prediction block. That is, the prediction unit predicts the pixel value of each pixel of the current block to be encoded in an image according to intra-prediction or inter-prediction, and generates a prediction block having a predicted pixel value of each pixel. In addition, the prediction unit can transmit information necessary for generating the prediction block to the encoding unit so that information about a prediction mode is encoded, and the information according to the information is included in a bitstream and transmitted to a decoder, and the decoding unit of the decoder parses the information to restore the information about the prediction mode, and then uses it for intra-prediction or inter-prediction. The subtraction unit subtracts the prediction block from the current block to generate a residual block. That is, the subtraction unit calculates the difference between the pixel value of each pixel of the current block to be encoded and the predicted pixel value of each pixel of the prediction block generated through the prediction unit, and generates a residual block, which is a residual signal in the form of a block. The transform unit can transform a signal belonging to the spatial domain into a signal belonging to the frequency domain, and the signal obtained through the transform process is called a transform coefficient. For example, a residual block having a residual signal received from a subtraction unit can be transformed to obtain a transform block having a transform coefficient. The input signal is determined according to the encoding settings, and this is not limited to the residual signal. The transformation unit can transform the residual block using transformation techniques such as Hadamard Transform, Discrete Sine Transform (DST Based-Transform), Discrete Cosine Transform (DCT Based-Transform), etc., but is not limited thereto and various transformation techniques that are improved and modified therefrom can be used. For example, at least one of the above transformation techniques may be supported, and at least one detailed transformation technique may be supported in each transformation technique. At this time, at least one detailed transformation technique may be a transformation technique in which a part of the basis vector is configured differently in each transformation technique. For example, a DST-based transformation and a DCT-based transformation may be supported as the transformation techniques, and in the case of DST, detailed transformation techniques such as DST-I, DST-II, DST-III, DST-V, DST-VI, DST-VII, and DST-VIII may be supported, and in the case of DCT, detailed transformation techniques such as DCT-I, DCT-II, DCT-III, DCT-V, DCT-VI, DCT-VII, and DCT-VIII may be supported. Among the above transformations, one transformation (e.g., one transformation technique && one detailed transformation technique) can be set as the basic transformation technique, and additional transformation techniques (e.g., multiple transformation techniques || multiple detailed transformation techniques) can be supported. Whether additional transformation techniques are supported is determined in units such as sequences, pictures, slices, tiles, etc., and related information can be generated in the units, and when additional transformation technique support is supported, transformation technique selection information can be determined in units such as blocks, etc., and related information can be generated. The transformation can be performed in the horizontal / vertical direction. For example, by performing a one-dimensional transformation in the horizontal direction and a one-dimensional transformation in the vertical direction using the basis vector in the transformation, a total of two-dimensional transformation can be performed to transform the pixel values ​​in the spatial domain into the frequency domain. In addition, the transformation in the horizontal / vertical direction can be performed adaptively. In detail, whether or not to perform adaptively can be determined depending on at least one encoding setting. For example, in the case of intra-screen prediction, if the prediction mode is horizontal mode, DCT-I can be applied in the horizontal direction and DST-I can be applied in the vertical direction, if it is vertical mode, DST-VI can be applied in the horizontal direction and DCT-VI can be applied in the vertical direction, if it is diagonal down left, DCT-II can be applied in the horizontal direction and DCT-V can be applied in the vertical direction, and if it is diagonal down right, DST-I can be applied in the horizontal direction and DST-VI can be applied in the vertical direction. The size and shape of each transform block are determined based on the candidate encoding cost of the size and shape of the transform block, and information such as image data of each determined transform block and the size and shape of each determined transform block can be encoded. Among the above transformation forms, a square transformation may be set as the basic transformation form, and additional transformation forms (e.g., rectangular shapes) may be supported. Whether additional transformation forms are supported is determined by units such as sequences, pictures, slices, and tiles, and related information may be generated by the above units, and transformation form selection information may be determined by units such as blocks, and related information may be generated. In addition, the support of the transformation block form can be determined according to the encoding information. At this time, the encoding information can correspond to the slice type, the encoding mode, the block size and shape, the block division method, etc. In other words, one transformation form can be supported according to at least one encoding information, and multiple transformation forms can be supported according to at least one encoding information. The former may be an implicit situation, and the latter may be an explicit situation. In the explicit case, adaptive selection information indicating an optimal candidate group among multiple candidates may be generated and included in the bitstream. In the present invention including this example, when the encoding information is explicitly generated, it can be understood that the corresponding information is included in the bitstream in various units, and the decoder parses the related information in various units and restores it as decoding information. In addition, when the sub / decoding information is implicitly processed, it can be understood that the encoder and decoder process it using the same process, rule, etc. For example, support for rectangular transformations may be determined based on the slice type. In the case of an I slice, the supported transformation type may be a square transformation, and in the case of a P / B slice, the supported transformation type may be a square or rectangular transformation. For example, support for rectangular transformations may be determined depending on the encoding mode. If it is Intra, the supported transformation type may be a square transformation, and if it is Inter, the supported transformation type may be a square or rectangular transformation. For example, support for rectangular transformations may be determined based on the size and shape of the block. The transformation type supported for blocks larger than a certain size may be a square transformation, and the transformation type supported for blocks smaller than a certain size may be a square or rectangular transformation. For example, support for rectangular transformation may be determined based on the block division method. If the block on which transformation is performed is a block obtained through a Quad Tree division method, the supported transformation may be a square transformation, and if the block is obtained through a Binary Tree division method, the supported transformation may be a square or rectangular transformation. The above example is an example of support for a transformation form according to a single encoding information, and multiple pieces of information may be combined to participate in setting additional transformation form support. The above example is only an example of support for additional transformation forms according to various encoding settings, and is not limited thereto, and various examples of modifications may be possible. The conversion process can be omitted depending on the encoding settings or the characteristics of the image. For example, the conversion process (including the inverse process) can be omitted depending on the encoding settings (assuming a lossless compression environment in this example). As another example, the conversion process can be omitted if the compression performance through conversion is not achieved depending on the characteristics of the image. In this case, the omitted conversion can be the entire unit, or one of the horizontal and vertical units can be omitted, and whether or not such omission is supported can be determined depending on the size and shape of the block. For example, in a setting where omission of horizontal and vertical transformations is tied, if the transformation omission flag is 1, transformation is not performed in the horizontal or vertical directions, and if it is 0, transformation can be performed in the horizontal or vertical directions. In a setting where omission of horizontal and vertical transformations operates independently, if the first transformation omission flag is 1, transformation is not performed in the horizontal direction, and if it is 0, transformation is performed in the horizontal direction, and if the second transformation omission flag is 1, transformation is not performed in the vertical direction, and if it is 0, transformation is performed in the vertical direction. When the block size falls within range A, transformation omission may be supported, and when it falls within range B, transformation omission may not be supported. For example, when the horizontal length of the block is greater than M or the vertical length of the block is greater than N, the transformation omission flag may not be supported, and when the horizontal length of the block is less than m or the vertical length of the block is less than n, the transformation omission flag may be supported. M(m) and N(n) may be the same or different. The transformation-related settings may be determined in units such as sequences, pictures, and slices. If an additional transformation technique is supported, the transformation technique setting can be determined based on at least one piece of encoding information. At this time, the encoding information can correspond to a slice type, an encoding mode, a block size and shape, a prediction mode, etc. For example, the support of the transformation technique may be determined according to the encoding mode. In the case of Intra, the supported transformation techniques may be DCT-I, DCT-III, DCT-VI, DST-II, and DST-III, and in the case of Inter, the supported transformation techniques may be DCT-II, DCT-III, and DST-III. For example, the support of transformation techniques may be determined according to the slice type. In the case of an I slice, the supported transformation techniques may be DCT-I, DCT-II, and DCT-III, in the case of a P slice, the supported transformation techniques may be DCT-V, DST-V, and DST-VI, and in the case of a B slice, the supported transformation techniques may be DCT-I, DCT-II, and DST-III. For example, the support of the transformation technique may be determined according to the prediction mode. The transformation technique supported in prediction mode A may be DCT-I, DCT-II, the transformation technique supported in prediction mode B may be DCT-I, DST-I, and the transformation technique supported in prediction mode C may be DCT-I. In this case, prediction modes A and B may be directional modes, and prediction mode C may be non-directional modes. For example, the support of the transformation technique may be determined according to the size and shape of the block. The transformation technique supported in blocks larger than a certain size may be DCT-II, the transformation technique supported in blocks smaller than a certain size may be DCT-II, DST-V, and the transformation technique supported in blocks larger than a certain size and smaller than a certain size may be DCT-I, DCT-II, DST-I. In addition, the transformation technique supported in a square shape may be DCT-I, DCT-II, and the transformation technique supported in a rectangular shape may be DCT-I, DST-I. The above example is an example of support for a transformation technique according to a single encoding information, and multiple pieces of information may be combined to participate in setting additional transformation technique support. It is not limited to the above example, and modifications to other examples may also be possible. In addition, the transformation unit may transmit information necessary for generating a transformation block to the encoding unit to encode it, and include the information accordingly in a bitstream and transmit it to the decoder, and the decoding unit of the decoder may parse the information and use it in the reverse transformation process. The quantization unit can quantize the input signal, and the signal obtained through the quantization process is called a quantized coefficient. For example, a residual block having residual transform coefficients received from a transform unit can be quantized to obtain a quantized block having quantized coefficients. The input signal is determined according to the encoding settings, and is not limited to the residual transform coefficients. The quantization unit can quantize the transformed residual block using a quantization technique such as Dead Zone Uniform Threshold Quantization, Quantization Weighted Matrix, etc., but is not limited thereto, and various quantization techniques that are improved and modified thereof can be used. Whether or not additional quantization techniques are supported is determined in units such as sequences, pictures, slices, and tiles, and related information can be generated in units such as the above, and when additional quantization techniques are supported, quantization technique selection information can be determined in units such as blocks, and related information can be generated. If additional quantization techniques are supported, the quantization technique setting can be determined based on at least one piece of encoding information. At this time, the encoding information can correspond to a slice type, an encoding mode, a block size and shape, a prediction mode, etc. For example, the quantization unit may apply different quantization weight matrices for inter-screen prediction / intra-screen prediction depending on the encoding mode. In addition, the weight matrices applied may be applied differently depending on the intra-screen prediction mode. In this case, the quantization weight matrix may be a quantization matrix in which some of the quantization components are configured differently, assuming that the block size is the same as the quantization block size with a size of M×N. The quantization process can be omitted depending on the encoding settings or the characteristics of the image. For example, the quantization process (including the inverse process) can be omitted depending on the encoding settings (assuming a lossless compression environment in this example). As another example, the quantization process can be omitted if the compression performance through quantization is not achieved depending on the characteristics of the image. In this case, the omitted area can be the entire area or a part of the area can be omitted, and whether or not such omission is supported can be determined depending on the size and shape of the block, etc. Information about quantization parameters (QP) can be generated in units such as sequences, pictures, slices, tiles, and blocks. For example, a default QP can be set in the upper unit where QP information is first generated. <1> , the QP can be set to the same or different value as the QP set in the upper unit as it goes down to the lower unit. <2> . Through this process, QP can be finally determined in the quantization process performed in some units. <3> . At this time, units such as sequences and pictures <1> Units such as slices, tiles, blocks, etc. <2> Units such as blocks, etc. <3> This may be an example of the corresponding case. Information about QP can be generated based on QP in each unit. Alternatively, differential information with respect to QP in each unit can be generated by setting a preset QP as a predicted value. Alternatively, differential information with respect to QP in the current unit can be generated by setting a QP obtained based on at least one of a QP set in a higher unit, a QP set in a previous identical unit, or a QP set in a neighboring unit as a predicted value. Alternatively, differential information with respect to QP in the current unit can be generated by setting a QP obtained based on the QP set in a higher unit and at least one piece of encoding information as a predicted value. In this case, the previous identical unit can be a unit that can be defined according to the encoding order of each unit, and the neighboring unit can be a spatially adjacent unit, and the encoding information can be a slice type, an encoding mode, a prediction mode, position information, etc. of the corresponding unit. For example, the QP of the current unit can generate differential information by setting the QP of the upper unit as the predicted value. The differential information between the QP set in the slice and the QP set in the picture can be generated, or the differential information between the QP set in the tile and the QP set in the picture can be generated. In addition, the differential information between the QP set in the block and the QP set in the slice or tile can be generated. In addition, the differential information between the QP set in the sub block and the QP set in the block can be generated. For example, the QP of the current unit can generate differential information by setting the QP obtained based on the QP of at least one neighboring unit or the QP obtained based on the QP of at least one previous unit as a predicted value. The differential information with respect to the QP obtained based on the QP of the neighboring block to the left, upper left, lower left, upper, upper right, etc. of the current block can be generated. Alternatively, the differential information with respect to the QP of the encoded picture previous to the current picture can be generated. For example, the QP of the current unit can generate differential information by setting the QP obtained based on the QP of the upper unit and at least one encoding information as a predicted value. The differential information between the QP of the current block and the QP of the slice to be corrected according to the slice type (I / P / B) can be generated. Alternatively, the differential information between the QP of the current block and the QP of the tile to be corrected according to the encoding mode (Intra / Inter) can be generated. Alternatively, the differential information between the QP of the current block and the QP of the picture to be corrected according to the prediction mode (directional / non-directional) can be generated. Alternatively, the differential information between the QP of the current block and the QP of the picture to be corrected according to the position information (x / y) can be generated. At this time, the meaning of the correction may mean adding or subtracting in the form of an offset to the QP of the upper unit used for prediction. At this time, at least one offset information may be supported according to the encoding setting, and the related information may be implicitly processed or explicitly generated according to a preset process. It is not limited to the above examples and variations to other examples may also be possible. The above example may be a possible example when a signal indicating QP variation is provided or activated. For example, when a signal indicating QP variation is not provided or is deactivated, the differential information is not generated and the predicted QP may be determined as the QP of each unit. In another example, when a signal indicating QP variation is provided or activated, the differential information is generated and when its value is 0, the predicted QP may also be determined as the QP of each unit. The quantization unit can transmit information required to generate a quantization block to the encoding unit to encode it, and can include the corresponding information in a bitstream and transmit it to the decoder, and the decoding unit of the decoder can parse the information and use it in the dequantization process. Although the above example was explained under the assumption that the residual block is transformed and quantized through the transform unit and the quantization unit, the residual block may be transformed into a residual signal to generate a residual block having transform coefficients without performing the quantization process, and the residual signal of the residual block may not be transformed into a transform coefficient and only the quantization process may be performed, and neither the transform nor the quantization process may be performed. This may be determined according to the encoder settings. The encoding unit may scan quantization coefficients, transform coefficients, or residual signals of a generated residual block according to at least one scan order (e.g., zigzag scan, vertical scan, horizontal scan, etc.) to generate a quantization coefficient series, a transform coefficient series, or a signal series, and may encode the scans using at least one entropy coding technique. At this time, information about the scan order may be determined according to an encoding setting (e.g., an encoding mode, a prediction mode, etc.), and may be implicitly determined or the related information may be explicitly generated. For example, one of a plurality of scan orders may be selected according to an intra-screen prediction mode. In addition, encoded data including encoded information transmitted from each component can be generated and output as a bitstream, and this can be implemented with a multiplexer (MUX). At this time, encoding can be performed using a method such as Exponential Golomb, Context Adaptive Variable Length Coding (CAVLC), Context Adaptive Binary Arithmetic Coding (CABAC), etc., and is not limited thereto, and various encoding techniques that are improved and modified therefrom can be used. When performing entropy encoding (assumed to be CABAC in this example) on syntactic elements such as the residual block data and information generated in the encoding / decoding process, the entropy encoding device may include a binarizer, a context modeler, and a binary arithmetic coder. At this time, the binary arithmetic coder may include a regular coding engine and a bypass coding engine. Since the syntax elements input to the above entropy encoding device may not be binary values, if the syntax elements are not binary values, the binarization unit can binarize the syntax elements and output an empty string (Bin String) consisting of 0 or 1. At this time, the bin represents a bit consisting of 0 or 1 and can be encoded through a binary arithmetic encoding unit. At this time, one of the regular coding unit or the bypass coding unit can be selected based on the occurrence probability of 0 and 1, and this can be determined according to the encoding / decoding settings. If the syntax elements are data having the same frequency of 0 and 1, the bypass coding unit can be used, and otherwise, the regular coding unit can be used. When performing binarization on the above syntax elements, various methods can be used. For example, fixed length binarization, unary binarization, truncated rice binarization, K-th Exp-Golomb binarization, etc. can be used. In addition, signed binarization or unsigned binarization can be performed depending on the range of values ​​that the syntax elements have. The binarization process for the syntax elements occurring in the present invention can be performed including not only the binarization mentioned in the above example but also other additional binarization methods. The inverse quantization unit and the inverse transform unit can be implemented by performing the processes in the transformation unit and the quantization unit in reverse. For example, the inverse quantization unit can inverse quantize the quantized transform coefficients generated by the quantization unit, and the inverse transform unit can inversely transform the inverse quantized transform coefficients to generate a restored residual block. The addition unit adds the prediction block and the restored residual block to restore the current block. The restored block is stored in memory and can be used as reference data (such as the prediction unit and filter unit). The in-loop filter unit may include at least one post-processing filter process, such as a deblocking filter, a sample adaptive offset (SAO), and an adaptive loop filter (ALF). The deblocking filter may remove block distortion occurring at a boundary between blocks in a restored image. The ALF may perform filtering based on a value obtained by comparing the restored image with an input image. Specifically, filtering may be performed based on a value obtained by comparing the restored image with an input image after a block is filtered through the deblocking filter. Alternatively, filtering may be performed based on a value obtained by comparing the restored image with an input image after a block is filtered through the SAO. The SAO restores an offset difference based on a value obtained by comparing the restored image with the input image, and may be applied in the form of a band offset (BO), an edge offset (EO), etc. Specifically, the SAO adds an offset from an original image in units of at least one pixel to a restored image to which a deblocking filter is applied, and may be applied in the form of a BO, an EO, etc. In detail, for the restored image after the block is filtered through ALF, an offset from the original image is added on a pixel basis, and can be applied in the form of BO, EO, etc. The setting information on whether each post-processing filter is supported can be generated in units of sequence, picture, slice, tile, etc. as filtering-related information. In addition, the setting information on whether each post-processing filter is performed can be generated in units of picture, slice, tile, block, etc. The range to which the filter is performed can be divided into the inside of the image and the boundary of the image, and the setting information considering this can be generated. In addition, the information related to the filtering operation can be generated in units of picture, slice, tile, block, etc. The information can be processed implicitly or explicitly, and the filtering can be applied as an independent filtering process or a dependent filtering process depending on the color component, and this can be determined according to the encoding setting. The in-loop filter unit can transmit the filtering-related information to the encoding unit to encode it, and include the information accordingly in a bitstream and transmit it to the decoder, and the decoding unit of the decoder can parse the information and apply it to the in-loop filter unit. The memory can store the restored block or picture. The restored block or picture stored in the memory can be provided to a prediction unit that performs intra-screen prediction or inter-screen prediction. Specifically, a storage space in the form of a queue of compressed bitstreams in an encoder can be processed as a coded picture buffer (CPB), and a space for storing a decoded image in picture units can be processed as a decoded picture buffer (DPB). In the case of the CPB, decoding units are stored according to the decoding order, and a decoding operation is emulated within the encoder, and a compressed bitstream can be stored during the emulation process, a bitstream output from the CPB is restored through a decoding process, and the restored image is stored in the DPB, and the pictures stored in the DPB can be referenced during subsequent image encoding and decoding processes. The decoding unit can be implemented by performing the process in reverse of the encoding unit. For example, it can receive a quantization coefficient series, a transform coefficient series, or a signal series from a bitstream, decode it, and parse the decoding data including the decoding information and transmit it to each component. The following describes an image setting process applied to an image encoding / decoding device according to an embodiment of the present invention. This may be an example applied to a stage before performing encoding / decoding (image initial setting), but some processes may be examples that may be applied to other stages (for example, a stage after performing encoding / decoding or an internal stage of encoding / decoding, etc.). The image setting process may be performed in consideration of network and user environments such as the characteristics of multimedia content, bandwidth, performance and accessibility of user terminals. For example, image segmentation, image size adjustment, image reconstruction, etc. may be performed according to the encoding / decoding settings. The image setting process described below is described based on a rectangular image, but is not limited thereto and may be applied to a polygonal image. Regardless of the shape of the image, the same image settings may be applied or different image settings may be applied, which may be determined according to the encoding / decoding settings. For example, after confirming information on the shape of the image (for example, rectangular or non-rectangular), information on image settings may be configured accordingly. In the examples described below, it will be assumed that settings are dependent on the color space, but it is also possible to have settings that are independent of the color space. In addition, in the examples described below, in the case of independent settings, examples of independently setting the encoding / decoding settings in each color space can be included, and even if an explanation is given for one color space, it is assumed and derived that examples are applied to other color spaces (for example, if M is generated from the luminance component, N is generated from the chrominance component). In addition, in the case of dependent settings, examples of proportional settings according to the composition ratio of the color format (for example, 4:4:4, 4:2:2, 4:2:0, etc.) can be included (for example, if M is in the luminance component in the case of 4:2:0, then M / 2 is in the chrominance component), and it is assumed and derived that examples are applied to each color space even without special explanation. This is not limited to the above examples, and may be a description commonly applied to the present invention. Some of the configurations in the examples described below may be applicable to various encoding techniques, such as encoding in the spatial domain, encoding in the frequency domain, block-based encoding, and object-based encoding. It may be common to perform encoding / decoding as is on the input image, but there may also be cases where the image is divided and then decoded. For example, the division may be performed for error robustness, etc., in order to prevent damage due to packet damage during transmission. Or, the division may be performed for the purpose of classifying areas with different properties within the same image according to the characteristics, type, etc. of the image. In the present invention, the image segmentation process can be performed by performing the segmentation process and the reverse process thereof. In the examples described below, the segmentation process is explained mainly, but the details of the reverse segmentation process can be derived from the segmentation process. Figure 3 is an example of dividing image information into layers to compress the image. 3a is an example of configuring a sequence of images into multiple GOPs. One GOP may be composed of I pictures, P pictures, and B pictures, as in 3b. One picture may be composed of slices, tiles, etc., as in 3c. The slices, tiles, etc. are composed of multiple basic coding units, as in 3d, and the basic coding unit may be composed of at least one lower coding unit, as in FIG. 3e. The image setting process in the present invention will be explained based on examples applied to units such as pictures, slices, and tiles, as in 3b and 3c. FIG. 4 is a conceptual diagram illustrating several examples of image segmentation according to one embodiment of the present invention. 4a is a conceptual diagram of dividing an image (e.g., a picture) into equal length intervals in the horizontal and vertical directions. The divided area can be referred to as a block, and each block can be a basic coding unit (or maximum coding unit) obtained through the picture dividing section, and can also be a basic unit applied in the dividing unit described later. 4b is a conceptual diagram that divides an image in at least one of the horizontal and vertical directions. The divided regions (T0 to T3) can be referred to as tiles, and each region can perform encoding / decoding that is independent or dependent on other regions. 4c is a conceptual diagram that divides an image into a group of consecutive blocks. The divided regions (S0, S1) can be referred to as slices, and each region can be a region that performs sub / decoding that is independent or dependent on other regions. The grouping of consecutive blocks can be defined according to the scan order, and generally follows the raster scan order, but is not limited thereto, and can be determined according to the sub / decoding settings. 4D is a conceptual diagram that divides an image into a group of blocks with arbitrary settings according to user definition. The divided areas (A0 to A2) can be referred to as arbitrary partitions, and each area can be an area that performs independent or dependent encoding / decoding of other areas. Independent encoding / decoding may mean that data of other units cannot be referenced when encoding / decoding some units (or regions). Specifically, information used or generated in texture encoding and entropy encoding of some units is encoded independently without reference to each other, and parsing information and restoration information of other units may not be referenced to each other in the decoder for texture decoding and entropy decoding of some units. At this time, whether data of other units (or regions) can be referenced may be limited in the spatial domain (for example, between regions within an image), but may also be limited in the temporal domain (for example, between consecutive images or frames) depending on the encoding / decoding settings. For example, if some units of the current image and some units of another image have continuity or have the same encoding environment, they may be referenced, and if not, the reference may be limited. In addition, dependent encoding / decoding may mean that data of other units can be referenced when encoding / decoding some units. Specifically, information used or generated in texture encoding and entropy encoding of some units is encoded dependently by referencing each other, and in the decoder, parsing information and restoration information of other units can also be referenced each other for texture decoding and entropy decoding of some units. In other words, it may be the same or similar settings as general encoding / decoding. In this case, depending on the characteristics, type, etc. of the image (for example, a 360-degree image), the area (the surface generated according to the projection format in this example) <face>It may be divided for the purpose of identifying (etc.). In the above example, some units (slices, tiles, etc.) may have independent sub / decryption settings (e.g., independent slice segments), and some units may have dependent sub / decryption settings (e.g., dependent slice segments). The present invention will be described with a focus on independent sub / decryption settings. The basic encoding unit obtained through the picture partitioning section, such as 4a, can be divided into basic encoding blocks according to the color space, and the size and shape can be determined according to the characteristics and resolution of the image. The size or shape of the supported block is a length of the width and height that is an exponent of 2 (2). n ) is expressed as an N × N square shape (2 n x2 n . 256x256, 128x128, 64x64, 32x32, 16x16, 8x8, etc. (where n is an integer between 3 and 8), or M × N rectangular (2 m x2 n ) can be. For example, for 8k UHD-grade video, the input video can be split into sizes such as 128x128, for 1080p HD-grade video, 64x64, and for WVGA-grade video, 16x16. And for 360-degree video, the input video can be split into sizes such as 256x256. The basic coding unit can be split into lower coding units and encoded / decoded, and information about the basic coding unit can be transmitted as a bitstream in units such as sequences, pictures, slices, and tiles, which can be parsed by a decoder to restore related information. The image encoding method and the decoding method according to one embodiment of the present invention may include the following image segmentation steps. At this time, the image segmentation process may include an image segmentation instruction step, an image segmentation type identification step, and an image segmentation performance step. In addition, the image encoding device and the decoding device may be configured to include an image segmentation instruction unit, an image segmentation type identification unit, and an image segmentation performance unit that implement the image segmentation instruction step, the image segmentation type identification step, and the image segmentation performance step. In the case of encoding, related syntax elements may be generated, and in the case of decoding, related syntax elements may be parsed. In each block segmentation process of 4a, the image segmentation instruction part may be omitted, and the image segmentation type identification part may be a process of confirming information about the size and shape of the block, and segmentation can be performed in the image segmentation part as a basic encoding unit through the identified segmentation type information. For blocks, it can always be the unit where the division is performed, while for other division units (tiles, slices, etc.), whether or not to divide can be determined based on the encoding / decoding settings. The picture division unit can perform division of other units after performing division of blocks as a default setting. In this case, block division can be performed based on the size of the picture. In addition, it can be divided into block units after being divided into other units (tiles, slices, etc.). That is, block division can be performed based on the size of the division unit. This can be determined through explicit or implicit processing depending on the encoding / decoding settings. In the examples described below, the former case is assumed and the explanation is centered on units other than blocks. In the image segmentation instruction step, it is possible to determine whether to perform image segmentation. For example, if a signal indicating image segmentation (e.g., tiles_enabled_flag) is confirmed, segmentation can be performed, and if a signal indicating image segmentation is not confirmed, segmentation can be not performed or segmentation can be performed by checking other sub / decoding information. In detail, if a signal instructing image segmentation (e.g., tiles_enabled_flag) is confirmed and the signal is activated (e.g., tiles_enabled_flag = 1), segmentation can be performed in multiple units, and if the signal is deactivated (e.g., tiles_enabled_flag = 0), segmentation may not be performed. Alternatively, if the signal instructing image segmentation is not confirmed, it may mean not performing segmentation or performing segmentation in at least one unit, and whether segmentation is performed in multiple units can be confirmed through another signal (e.g., first_slice_segment_in_pic_flag). In summary, when a signal instructing image segmentation is provided, the signal is a signal for indicating whether to segment into multiple units, and whether to segment the image can be determined based on the signal. For example, when tiles_enabled_flag is a signal indicating whether to segment the image, if tiles_enabled_flag is 1, it can mean that the image is segmented into multiple tiles, and if it is 0, it can mean that the image is not segmented. In summary, if a signal indicating image segmentation is not provided, segmentation may not be performed, or whether the image is segmented may be determined by another signal. For example, first_slice_segment_in_pic_flag is not a signal indicating whether the image is segmented, but rather a signal indicating whether it is the first slice segment in the image. However, through this, it is possible to determine whether the image is segmented into two or more units (for example, if the flag is 0, it means that the image is segmented into multiple slices). It is not limited to the above example, and variations to other examples may also be possible. For example, a signal instructing image segmentation in a tile may not be provided, and a signal instructing image segmentation in a slice may be provided. Alternatively, a signal instructing image segmentation may be provided based on the type, characteristics, etc. of the image. In the image segmentation type identification step, the image segmentation type can be identified. The image segmentation type can be defined by the method of performing segmentation, segmentation information, etc. In 4b, a tile can be defined as a unit obtained by dividing in the horizontal and vertical directions. Specifically, it can be defined as a group of adjacent blocks within a rectangular space demarcated by at least one horizontal or vertical dividing line running across the image. The segmentation information for the tiles may include boundary position information of rows and columns, number of tiles in the rows and columns, size information of the tiles, etc. The number of tiles information may include the number of rows (e.g., num_tile_columns) and the number of columns (e.g., num_tile_rows) of the tiles, through which the tiles may be segmented into (number of rows × number of columns). The size information of the tiles may be acquired based on the number of tiles information, and the width or height of the tiles may be uniform or unequal, which may be implicitly determined under a preset rule or may explicitly generate related information (e.g., uniform_spacing_flag). In addition, the size information of the tiles may include size information of each row and column of the tiles (e.g., column_width_tile[i], row_height_tile[i]) or may include width and height size information of each tile. Additionally, the above size information may be information that can be additionally generated depending on whether the tile size is uniform (for example, when uniform_spacing_flag is 0, indicating uneven division). In 4c, a slice can be defined as a group of consecutive blocks. Specifically, it can be defined as a group of consecutive blocks based on a preset scan order (raster scan in this example). The segmentation information for a slice may include information on the number of slices, location information of the slice (e.g., slice_segment_address), etc. At this time, the location information of the slice may be location information of a block that is preset (e.g., the first order in the scan order within the slice), and at this time, the location information may be scan order information of the block. In 4D, any partition area can have various partition settings. In 4D, a partition unit can be defined as a group of spatially adjacent blocks, and partition information for the same can include information on the size, shape, and location of the partition unit. These are just some examples of arbitrary partition areas, and various partition shapes are possible, as shown in Fig. 5. FIG. 5 is another example of an image segmentation method according to one embodiment of the present invention. For 5a and 5b, an image can be divided into multiple regions with at least one block interval in the horizontal or vertical direction, and the division can be performed based on block position information. 5a shows an example (A0, A1) in which division is performed based on vertical column information of each block in the horizontal direction, and 5b shows an example (B0 to B3) in which division is performed based on horizontal and vertical column information of each block in the horizontal and vertical directions. The division information for this can include the number of division units, block interval information, division direction, etc., and if this is implicitly included according to a preset rule, some of the division information may not be generated. For 5c and 5d, the image can be segmented into a group of consecutive blocks based on the scan order. An additional scan order other than the raster scan order of the existing slice can be applied to the image segmentation. 5c represents an example (C0, C1) in which scanning (Box-Out) is performed clockwise or counterclockwise centered on the start block, and 5d represents an example (D0, D1) in which scanning (Vertical) is performed centered on the start block. The segmentation information for this may include information on the number of segmentation units, information on the position of the segmentation units (for example, the first order in the scan order within the segmentation unit), information on the scan order, etc., and if this is implicitly included according to a preset rule, some segmentation information may not be generated. In the case of 5e, the image can be divided by horizontal and vertical dividing lines. Existing tiles can be divided by horizontal or vertical dividing lines and have a rectangular space division shape accordingly, but division across the image by the dividing lines may not be possible. For example, an example of division across the image along some dividing lines of the image (for example, a dividing line that forms the right boundaries of E1, E3, and E4 and the left boundary of E5) may be possible, and an example of division across the image along some dividing lines of the image (for example, a dividing line that forms the lower boundaries of E2 and E3 and the upper boundary of E4) may not be possible. In addition, division may be performed based on block units (for example, block division may be performed first and then divided) or division may be performed by the horizontal or vertical dividing lines, etc. (for example, division by the dividing lines regardless of block division), and accordingly, each division unit may not be composed of an integer multiple of blocks. Accordingly, segmentation information different from the existing tiles may be generated, and the segmentation information may include information on the number of segmentation units, position information of the segmentation units, size information of the segmentation units, etc. For example, the position information of the segmentation unit may generate position information (e.g., measured in pixel units or block units) based on a preset position (e.g., the upper left corner of the image), and the size information of the segmentation unit may generate horizontal and vertical size information of each segmentation unit (e.g., measured in pixel units or block units). As in the above example, segmentation with arbitrary settings according to user definition can be performed by applying a new segmentation method, or it can be performed by changing and applying some configurations of existing segmentation. That is, it can be supported as a segmentation form that replaces or adds to an existing segmentation method, or it can be supported as a form in which some settings are changed in an existing segmentation method (slice, tile, etc.) (for example, following a different scan order, a different segmentation method in a square shape, and generating different segmentation information accordingly, dependent loading / decoding characteristics, etc.). In addition, settings that configure additional segmentation units (for example, settings other than segmenting according to the scan order or segmenting according to a certain interval difference) can be supported, and additional segmentation unit shapes (for example, dividing into a polygonal shape such as a triangle rather than a square space) can be supported. In addition, an image segmentation method can be supported based on the type, characteristics, etc. of the image. For example, some segmentation methods (for example, the surface of a 360-degree image) can be supported depending on the type, characteristics, etc. of the image, and segmentation information can be generated based on this. In the image segmentation performance step, the image can be segmented based on the identified segmentation type information. That is, segmentation can be performed into multiple segmentation units based on the identified segmentation type, and encoding / decoding can be performed based on the acquired segmentation units. At this time, depending on the split type, it is possible to determine whether the split unit has a sub / decoding setting. That is, the setting information required for the sub / decoding process of each split unit can be allocated from a higher unit (e.g., a picture), or the split unit can have an independent sub / decoding setting. In general, for a slice, it is possible to have an independent sub / decoding setting (e.g., a slice header) for each segmentation unit, and for a tile, it is not possible to have an independent sub / decoding setting for each segmentation unit, and it is possible to have a setting dependent on the sub / decoding setting of the picture (e.g., PPS). In this case, information generated in relation to the tile may be segmentation information, and this may be included in the sub / decoding setting of the picture. The present invention is not limited to the above case, and other modified examples may be possible. The sub / decoding setting information for a tile can be generated in units such as video, sequence, and picture, and at least one sub / decoding setting information can be generated in a higher unit and one of them can be referenced. Alternatively, independent sub / decoding setting information (e.g., tile header) can be generated in units of tiles. This is different from following one sub / decoding setting determined in a higher unit in that sub / decoding is performed by setting at least one sub / decoding setting in units of tiles. That is, all tiles can follow one sub / decoding setting, or sub / decoding can be performed in at least one tile by following a different sub / decoding setting from other tiles. Although the above examples focus on various encrypting / decrypting settings in tiles, they are not limited to this and similar or identical settings can be applied to other partition types. For example, some partition types can generate partition information in a higher unit and perform sub-encryption / decryption according to one sub-encryption / decryption setting of the higher unit. For example, some types of partitioning can generate partitioning information in a higher unit, generate independent sub-encryption / decryption settings for each partitioning unit in the higher unit, and perform sub-encryption / decryption accordingly. For example, some partition types can generate partition information in a higher unit, support multiple sub / decryption setting information in the higher unit, and perform sub / decryption according to the sub / decryption setting referenced in each partition unit. For example, some types of partitioning can generate partitioning information in a higher unit, generate independent sub / decryption settings in that partitioning unit, and perform sub / decryption accordingly. For example, some split types can generate independent sub / decryption settings including split information in the corresponding split unit and perform sub / decryption accordingly. The sub / decoding setting information may include information required for sub / decoding of a tile, such as a tile type, information about a picture list to be referenced, quantization parameter information, inter-screen prediction setting information, in-loop filtering setting information, in-loop filtering control information, scan order, and whether sub / decoding is performed. The sub / decoding setting information may explicitly generate related information, or settings for sub / decoding may be implicitly determined according to the format, characteristics, etc. of an image determined in a higher unit. In addition, related information may be explicitly generated based on information acquired with the above settings. The following shows an example of performing image segmentation in an encoding / decoding device according to one embodiment of the present invention. A segmentation process can be performed on the input image before encoding begins. After segmentation is performed using segmentation information (e.g., image segmentation information, segmentation unit setting information, etc.), the image can be encoded in segmentation units. After encoding is completed, it can be stored in memory, and the image encoding data can be included in the bitstream and transmitted. A segmentation process can be performed before starting decryption. After segmentation is performed using segmentation information (e.g., image segmentation information, segmentation unit setting information, etc.), the image decryption data can be parsed and decoded by segmentation unit. After decryption is completed, it can be stored in memory, and multiple segmentation units can be merged into one to output the image. The segmentation process of an image has been described through the above example. In addition, multiple segmentation processes can be performed in the present invention. For example, segmentation can be performed on an image, and segmentation can be performed on a segmentation unit of the image, and the segmentation can be the same segmentation process (e.g., slice / slice, tile / tile, etc.) or a different segmentation process (e.g., slice / tile, tile / slice, tile / surface, surface / tile, slice / surface, surface / slice, etc.). At this time, a subsequent segmentation process can be performed based on a preceding segmentation result, and segmentation information generated in the subsequent segmentation process can be generated based on the preceding segmentation result. In addition, multiple segmentation processes (A) can be performed, and the segmentation processes can be different segmentation processes (e.g., slice / surface, tile / surface, etc.). At this time, the subsequent segmentation process can be performed based on the preceding segmentation result, or the segmentation process can be performed independently regardless of the preceding segmentation result, and the segmentation information generated in the subsequent segmentation process can be generated based on the preceding segmentation result or can be generated independently. The process of multiple segmentation of an image can be determined according to the encoding / decoding settings, and is not limited to the above examples, and various modified examples may also be possible. In the above process, the information generated will be recorded in the bitstream as at least one unit such as a sequence, picture, slice, or tile in the encoder, and the decoder will parse the related information from the bitstream. That is, it can be recorded in one unit, or it can be recorded in multiple units. For example, a syntax element for whether some information is supported or whether it is activated, etc., can be generated in some units (e.g., an upper unit), and information identical to or similar to the above case can be generated in some units (e.g., a lower unit). That is, even if the related information is supported and set in the upper unit, it can have individual settings in the lower unit. This is not limited to the above example, and can be a description commonly applied to the present invention. In addition, it can be included in the bitstream in the form of SEI or metadata. On the other hand, it may be common to perform encoding / decoding as is the input image, but there may also be cases where encoding / decoding is performed after adjusting the image size (expanding or reducing, adjusting the resolution). For example, in a hierarchical encoding method (Scalability Video Coding) to support spatial, temporal, and image quality scalability, image size adjustment such as overall expansion or reduction of the image can be performed. Or, image size adjustment such as partial expansion or reduction of the image can be performed. Image size adjustment is possible in various ways, and can be performed for the purpose of adaptability to the encoding environment, for the purpose of encoding consistency, for the purpose of encoding efficiency, for the purpose of improving image quality, or for the purpose of the type or characteristics of the image. As a first example, a resizing process may be performed in a process that proceeds depending on the characteristics, type, etc. of the image (e.g., hierarchical encoding, 360-degree image encoding, etc.). As a second example, the resizing process can be performed at the initial stage of encoding / decoding. The resizing process can be performed before encoding / decoding, and the image being resized can be encoded / decoded. As a third example, a resizing process can be performed before the prediction step (intra-screen prediction or inter-screen prediction) or before performing prediction. In the resizing process, image information from the prediction step (e.g., pixel information referenced for intra-screen prediction, information related to intra-screen prediction mode, reference image information used for inter-screen prediction, information related to inter-screen prediction mode, etc.) can be used. As a fourth example, a resizing process may be performed before performing the filtering step or filtering. In the resizing process, image information from the filtering step (e.g., pixel information applied to the deblocking filter, pixel information applied to SAO, information related to SAO filtering, pixel information applied to ALF, information related to ALF filtering, etc.) may be used. In addition, after the resizing process is performed, the image may or may not be changed to the image before resizing (in terms of the size of the image) through the inverse resizing process, which may be determined depending on the encoding / decoding settings (e.g., the nature of the resizing performed). In this case, if the resizing process is expansion, the inverse resizing process may be reduction, and if the resizing process is reduction, the inverse resizing process may be expansion. If the resizing process according to the first to fourth examples is performed, the resizing reverse process can be performed in a subsequent step to obtain an image before resizing. If the resizing process according to the hierarchical encoding or the third example has been performed (or the reference image has been resized in inter-screen prediction), the inverse resizing process may not be performed in subsequent steps. In one embodiment of the present invention, the image resizing process may be performed alone or inversely, and the following example will focus on the resizing process. In this case, the reverse resizing process is the opposite process of the resizing process, so the description of the reverse resizing process may be omitted to avoid redundant description, but it is clear that a person skilled in the art can recognize it as being the same as what is described literally. Figure 6 is an example of a general image resizing method. Referring to Fig. 6a, an extended image (P0+P1) can be obtained by additionally including some regions (P1) from the initial image (or the image before resizing. P0. Thick solid line). Referring to 6b, a reduced image (S0) can be obtained by excluding some areas (S1) from the initial image (S0+S1). Referring to 6c, a resized image (T0+T1) can be obtained by additionally including some regions (T1) and excluding some regions (T2) from the initial image (T0+T2). Hereinafter, the present invention will be described with a focus on the size adjustment process according to expansion and the size adjustment process according to reduction, but it should be understood that it is not limited thereto and includes a case where size expansion and reduction are applied in a mixed manner, such as 6c. FIG. 7 is an example diagram for image resizing according to one embodiment of the present invention. Referring to 7a, we can explain how to expand an image during the resizing process, and referring to 7b, we can explain how to reduce an image. In Fig. 7a, the image before resizing is S0, and the image after resizing is S1, and in Fig. 7b, the image before resizing is T0, and the image after resizing is T1. When expanding an image like 7a, it can be expanded in the up, down, left, and right directions (ET, EL, EB, ER), and when reducing an image like 7b, it can be reduced in the up, down, left, and right directions (RT, RL, RB, RR). When comparing image expansion and reduction, the up, down, left, and right directions in expansion can correspond to the down, up, right, and left directions in reduction, respectively. Therefore, the following explanation is based on image expansion, but it should be understood that the explanation for image reduction is included. Additionally, although image expansion or reduction in the up, down, left, and right directions is described below, it should be understood that resizing can be performed in the upper left, upper right, lower left, and lower right directions. At this time, when performing expansion in the lower right direction, RC and BC regions are acquired, while BR regions may or may not be acquired depending on the encoding / decoding settings. That is, TL, TR, BL, and BR regions may or may not be acquired, but for the sake of convenience of explanation, it is explained below that corner regions (TL, TR, BL, BR regions) are acquired. The image resizing process according to one embodiment of the present invention can be performed in at least one direction. For example, it can be performed in all of the up, down, left, and right directions, and can be performed in two or more directions selected from the up, down, left, and right directions (left+right, up+down, up+left, up+right, down+left, down+right, up+left+right, down+left+right, up+down+left, up+down+right, etc.), and only one direction from the up, down, left, and right directions can be performed. For example, the image may be sized in the left+right, up+down, top left+bottom right, bottom left+top right directions that are symmetrically expandable from the center of the image to both ends, the image may be sized in the left+right, top left+top right, bottom left+bottom right directions that are vertically symmetrically expandable, the image may be sized in the top+bottom, top left+bottom left, top right+bottom right directions that are horizontally symmetrically expandable, and other sizing directions may also be possible. In 7a and 7b, the size of the image (S0, T0) before resizing is defined as P_Width × P_Height, and the size of the image (S1, T1) after resizing is defined as P'_Width × P'_Height. Here, if the resize values ​​in the left, right, up, and down directions are defined as Var_L, Var_R, Var_T, and Var_B (or collectively referred to as Var_x), the size of the image after resizing can be expressed as (P_Width + Var_L + Var_R) × (P_Height + Var_T + Var_B). At this time, the left, right, up, down size adjustment values, Var_L, Var_R, Var_T, Var_B, can be Exp_L, Exp_R, Exp_T, Exp_B (Exp_x is a positive number in this example) in image expansion (Fig. 7a), and -Rec_L, -Rec_R, -Rec_T, -Rec_B (if Rec_L, Rec_R, Rec_T, Rec_B are defined as positive numbers, they are expressed as negative numbers according to image reduction) in image reduction. Also, the coordinates of the upper left, upper right, lower left, and lower right of the image before resizing are (0,0), (P_Width-1,0), (0,P_Height-1), (P_Width-1,P_Height-1), and the above coordinates of the image after resizing can be expressed as (0,0), (P'_Width-1,0), (0,P'_Height-1), (P'_Width-1,P'_Height-1). The size of the area (TL to BR in this example, where i is an index distinguishing TL to BR) that is changed (or acquired, removed) by resizing can be M[i] × N[i], which can be expressed as Var_X × Var_Y (X is assumed to be L or R, and Y is assumed to be T or B in this example). M and N can have various values, and can be the same regardless of i or have individual settings depending on i. Various cases for this will be described later. Referring to 7a, S1 can be configured by including all or part of TL to BR (upper left to lower right) generated through expansion in various directions to S0. Referring to 7b, T1 can be configured by excluding all or part of TL to BR removed through reduction in various directions to T0. In 7a, when performing expansion in the upper, lower, left, and right directions on an existing image (S0), an image can be configured including TC, BC, LC, and RC regions obtained according to each resizing process, and additionally, TL, TR, BL, and BR regions can be included. For example, when performing expansion in the upper (ET) direction, an image can be composed by including a TC region in the existing image (S0), and a TL or TR region can be included depending on expansion in at least one other direction (EL or ER). For example, when performing expansion in the downward (EB) direction, an image can be composed by including the BC region in the existing image (S0), and can include the BL or BR region depending on expansion in at least one other direction (EL or ER). For example, when performing expansion in the left (EL) direction, an image can be composed by including the LC region in the existing image (S0), and can include the TL or BL region depending on expansion in at least one other direction (ET or EB). For example, when performing expansion in the right (ER) direction, an image can be composed by including an RC region in the existing image (S0), and can include a TR or BR region depending on expansion in at least one other direction (ET or EB). According to one embodiment of the present invention, a setting (e.g., spa_ref_enabled_flag or tem_ref_enabled_flag) may be placed to spatially or temporally limit the referentiality of a resized area (assumed to be an extension in this example). That is, depending on the encoding / decoding settings, it is possible to reference data in areas that are spatially or temporally scaled (e.g., spa_ref_enabled_flag = 1 or tem_ref_enabled_flag = 1) or restrict references (e.g., spa_ref_enabled_flag = 0 or tem_ref_enabled_flag = 0). Encoding / decoding of images before resizing (S0, T1) and areas added or deleted during resizing (TC, BC, LC, RC, TL, TR, BL, BR areas) can be performed as follows. For example, in the decoding / encoding of an image before resizing and an area to be added or deleted, the data of the image before resizing and the data of the area to be added or deleted (data for which decoding / encoding is complete, such as pixel values ​​or prediction-related information) can be spatially or temporally referenced to each other. Alternatively, while the data of the image before resizing and the data of the region being added or deleted can be spatially referenced, the data of the image before resizing can be temporally referenced, and the data of the region being added or deleted cannot be temporally referenced. That is, a setting can be set to limit the referentiality of the area being added or deleted. The setting information on the referentiality of the area being added or deleted can be explicitly created or implicitly determined. An image resizing process according to one embodiment of the present invention may include an image resizing instruction step, an image resizing type identification step, and / or an image resizing execution step. In addition, an image encoding device and a decoding device may include an image resizing instruction unit, an image resizing type identification unit, and an image resizing execution unit that implement the image resizing instruction step, the image resizing type identification step, and the image resizing execution step. In the case of encoding, related syntax elements may be generated, and in the case of decoding, related syntax elements may be parsed. In the image resizing instruction step, it is possible to determine whether to perform image resizing. For example, if a signal instructing image resizing (e.g., img_resizing_enabled_flag) is confirmed, resizing can be performed, and if the signal instructing image resizing is not confirmed, resizing may not be performed or resizing may be performed by checking other sub / decoding information. In addition, even if a signal instructing image resizing is not provided, a signal instructing resizing may be implicitly activated or deactivated depending on sub / decoding settings (e.g., image characteristics, type, etc.), and if resizing is performed, resizing-related information may be generated accordingly or resizing-related information may be implicitly determined. When a signal instructing image resizing is provided, the signal is a signal indicating whether to resize the image, and whether to resize the image can be determined based on the signal. For example, if a signal indicating image resizing (e.g., img_resizing_enabled_flag) is identified and the signal is enabled (e.g., img_resizing_enabled_flag = 1), image resizing can be performed, and if the signal is disabled (e.g., img_resizing_enabled_flag = 0), image resizing can be performed. Additionally, if a signal instructing image resizing is not provided, resizing may not be performed, or it may be determined by another signal whether the image is resized. For example, when dividing an input image into blocks, resizing (in the case of expansion in this example, it is assumed that the resizing process is performed when it is not an integer) can be performed depending on whether the size (e.g., width or height) of the image is an integer multiple of the size (e.g., width or height) of the block. That is, resizing can be performed when the width of the image is not an integer multiple of the width of the block or when the height of the image is not an integer multiple of the height of the block. At this time, the resizing information (e.g., resizing direction, resizing value, etc.) can be determined according to the above-described encoding / decoding information (e.g., image size, block size, etc.). Alternatively, resizing can be performed according to the characteristics and type of the image (e.g., 360-degree image), and the resizing information can be explicitly generated or assigned as a preset value. It is not limited to the above example, and variations to other examples may also be possible. In the image resizing type identification step, the image resizing type can be identified. The image resizing type can be defined by the method of performing the resizing, the resizing information, etc. For example, resizing through a scale factor, resizing through an offset factor, etc. can be performed. The present invention is not limited thereto, and a case where the above methods are applied in combination may also be possible. For the convenience of explanation, the explanation will be centered on resizing through a scale factor and an offset factor. In the case of the scale factor, resizing can be performed by multiplying or dividing based on the size of the image. Information on the operation of resizing (e.g., expansion or reduction) can be explicitly generated, and the expansion or reduction process can be performed according to the information. In addition, the resizing process can be performed with a preset operation (e.g., one of expansion or reduction) depending on the encoding / decoding settings, and in this case, information on the resizing operation can be omitted. For example, if image resizing is activated in the image resizing instruction step, image resizing can be performed with a preset operation. The resizing direction may be at least one direction selected from the up, down, left, and right directions. At least one scale factor may be required depending on the resizing direction. That is, one scale factor (unidirectional in this example) may be required for each direction, one scale factor (bidirectional in this example) may be required depending on the horizontal or vertical direction, and one scale factor (omnidirectional in this example) may be required depending on the overall direction of the image. In addition, the resizing direction is not limited to the above examples and may also be modified to other examples. The scale factor can have a positive value, and the range information can be different depending on the encoding / decoding settings. For example, when generating information by mixing a resizing operation and a scale factor, the scale factor can be used as a multiplying value. If it is greater than 0 or less than 1, it can mean a shrinking operation, if it is greater than 1, it can mean an expansion operation, and if it is 1, it can mean that no resizing is performed. As another example, when generating scale factor information separately from a resizing operation, the scale factor can be used as a multiplying value in the case of an expansion operation, and the scale factor can be used as a dividing value in the case of a shrinking operation. Referring again to FIG. 7a and 7b, the process of changing from an image before resizing (S0, T0) to an image after resizing (S1, T1 in this example) using a scale factor can be explained. For example, if one scale factor (referred to as sc) is used along the entire direction of the image and the resizing direction is the down+right direction, the resizing direction is ER, EB (or RR, RB), the resizing values ​​Var_L (Exp_L or Rec_L) and Var_T (Exp_T or Rec_T) are 0, and Var_R (Exp_R or Rec_R) and Var_B (Exp_B or Rec_B) can be expressed as P_Width × (sc - 1), P_Height × (sc - 1). Therefore, the image after resizing can be (P_Width × sc) × (P_Height × sc). For example, if each scale factor (sc_w, sc_h in this example) is used according to the horizontal or vertical direction of the image, and the resizing direction is left+right, up+down (up+down+left+right if both operate), the resizing directions are ET, EB, EL, ER, and the resizing values ​​Var_T and Var_B can be P_Height×(sc_h - 1) / 2, and Var_L and Var_R can be P_Width×(sc_w - 1) / 2. Therefore, the image after resizing can be (P_Width×sc_w) × (P_Height×sc_h). For the offset factor, the resizing can be performed by adding or subtracting based on the size of the image. Or, the resizing can be performed by adding or subtracting based on the image's encoding / decoding information. Or, the resizing can be performed by adding or subtracting independently. In other words, the resizing process can be set dependently or independently. Information about a resizing operation (e.g., expansion or reduction) can be explicitly generated, and the expansion or reduction process can be performed according to the information. In addition, the resizing operation can be performed as a preset operation (e.g., one of expansion or reduction) according to the sub / decryption settings, and in this case, the information about the resizing operation can be omitted. For example, if image resizing is activated in the image resizing instruction step, image resizing can be performed as a preset operation. The resizing direction may be at least one of the up, down, left, and right directions. At least one offset factor may be required depending on the resizing direction. That is, one offset factor may be required for each direction (unidirectional in this example), one offset factor may be required depending on the horizontal or vertical direction (symmetrical bidirectional in this example), one offset factor may be required depending on a partial combination of each direction (asymmetrical bidirectional in this example), and one offset factor may be required depending on the overall direction of the image (omnidirectional in this example). In addition, the resizing direction is not limited to the above examples and may also be modified to other examples. The offset factor can have a positive value, or can have positive and negative values, and can have different range information depending on the encoding / decoding settings. For example, when generating information by mixing a resizing operation and an offset factor (assuming positive and negative values ​​in this example), the offset factor can be used as a value to be added or subtracted depending on the sign information of the offset factor. When the offset factor is greater than 0, it can mean an expansion operation, when it is less than 0, it can mean a reduction operation, and when it is 0, it can mean that no resizing is performed. As another example, when generating offset factor information separately from a resizing operation (assuming that it has a positive value in this example), the offset factor can be used as a value to be added or subtracted depending on the resizing operation. When it is greater than 0, it can mean that an expansion or reduction operation can be performed depending on the resizing operation, and when it is 0, it can mean that no resizing is performed. Referring again to FIG. 7a and FIG. 7b, a method of changing from an image (S0, T0) before resizing to an image (S1, T1) after resizing can be explained using an offset factor. For example, if one offset factor (referred to as os) is used along the entire direction of the image and the resizing direction is up+down+left+right, the resizing directions can be ET, EB, EL, ER (or RT, RB, RL, RR), and the resizing values ​​Var_T, Var_B, Var_L, Var_R can be os. The image size after resizing can be (P_Width+os)×(P_Height+os). For example, if each offset factor (os_w, os_h) is used according to the horizontal or vertical direction of the image, and the resize direction is left+right, up+down (up+down+left+right if both operate), the resize directions are ET, EB, EL, ER (or RT, RB, RL, RR), and the resize values ​​Var_T, Var_B can be os_h, and Var_L, Var_R can be os_w. The image size after resizing can be {P_Width+(os_w×2)}×{P_Height+(os_h×2)}. For example, if the resize direction is down, right (down+right when working together) and each offset factor (os_b, os_r) is used according to the resize direction, the resize direction is EB, ER (or RB, RR), and the resize value Var_B can be os_b, and Var_R can be os_r. The image size after resize can be (P_Width + os_r) × (P_Height + os_b). For example, if each offset factor (os_t, os_b, os_l, os_r) is used in each direction of the image and the resizing direction is up, down, left, right (up+down+left+right if all work), the resizing direction is ET, EB, EL, ER (or RT, RB, RL, RR), and the resizing value Var_T can be os_t, Var_B can be os_b, Var_L can be os_l, and Var_R can be os_r. The image size after resizing can be (P_Width + os_l + os_r) × (P_Height + os_t + os_b). The above example shows a case where an offset factor is used as a resizing value (Var_T, Var_B, Var_L, Var_R) in a resizing process. That is, the offset factor is used as a resizing value as it is, which may be an example of resizing performed independently. Alternatively, the offset factor may be used as an input variable of the resizing value. Specifically, an offset factor may be assigned as an input variable and a resizing value may be obtained through a series of processes according to the encoding / decoding settings, which may be an example of resizing performed based on preset information (e.g., image size, encoding / decoding information, etc.) or an example of resizing performed dependently. For example, the offset factor can be a multiple (e.g., 1, 2, 4, 6, 8, 16, etc.) or an exponent (e.g., a power of 2 such as 1, 2, 4, 8, 16, 32, 64, 128, 256, etc.) of a preset value (an integer in this example). Or, it can be a multiple or exponent of a value obtained based on the encoding / decoding settings (e.g., a value set based on a motion search range of inter-screen prediction). Or, it can be a multiple or exponent of a unit obtained from a picture partitioning unit (assumed to be A×B in this example). Or, it can be a multiple of a unit obtained from a picture partitioning unit (assumed to be E×F in this example because it is a tile). Alternatively, it may be a value in a range smaller than or equal to the width and height of the unit obtained from the picture segmentation section. The multiple or exponent of the above example may also include a case where the value is 1, and is not limited to the above example and may also be modified to another example. For example, if the offset factor is n, Var_x may be 2 × n or 2 n It could be. In addition, individual offset factors can be supported according to color components, and offset factors for some color components can be supported to derive offset factor information for other color components. For example, if an offset factor (A) for a luminance component (assuming that the ratio of the luminance component to the chrominance component is 2:1 in this example) is explicitly generated, an offset factor (A / 2) for a chrominance component can be implicitly obtained. Or, if an offset factor (A) for a chrominance component is explicitly generated, an offset factor (2A) for a luminance component can be implicitly obtained. Information about the resizing direction and the resizing value can be explicitly generated, and the resizing process can be performed according to the information. In addition, it can be implicitly determined according to the sub / decoding setting, and the resizing process can be performed accordingly. At least one preset direction or resizing value can be assigned, and in this case, the related information can be omitted. At this time, the sub / decoding setting can be determined based on the characteristics, type, encoding information, etc. of the image. For example, at least one resizing direction according to at least one resizing operation can be determined in advance, at least one resizing value according to at least one resizing operation can be determined in advance, and at least one resizing value according to at least one resizing direction can be determined in advance. In addition, the resizing direction and the resizing value in the resizing reverse process can be derived from the resizing direction and the resizing value applied in the resizing process. At this time, the resizing value implicitly determined can be one of the above-mentioned examples (examples in which various resizing values ​​are obtained). In addition, although the above example has described cases of multiplication and division, it can be implemented as a shift operation depending on the implementation of the encoder / decoder. In the case of multiplication, it can be implemented through a left shift operation, and in the case of division, it can be implemented through a right shift operation. This is not limited to the above example, and can be a description commonly applied to the present invention. In the image resizing performance step, image resizing can be performed based on the identified resizing information. That is, image resizing can be performed based on information such as resizing type, resizing operation, resizing direction, and resizing value, and encoding / decoding can be performed based on the acquired resized image. In addition, in the image resizing performing step, the resizing can be performed using at least one data processing method. Specifically, the resizing can be performed using at least one data processing method in the area to be resized depending on the resizing type and the resizing operation. For example, depending on the resizing type, if the resizing is expansion, it can be determined how to fill the data, or if the resizing process is reduction, it can be determined how to remove the data. In summary, image resizing can be performed based on the resizing information identified in the image resizing performing step. Alternatively, image resizing can be performed based on the resizing information and the data processing method in the image resizing performing step. The difference between the above two cases can be that only the resizing of the image to be encoded / decoded is performed, or the size of the image and the data processing of the resized area are considered. Whether to perform the image resizing performing step including the data processing method can be determined according to the application step, location, etc. of the resizing process. In the examples described below, the description will be centered on an example of performing resizing based on the data processing method, but is not limited thereto. When performing resizing via an offset factor, resizing can be performed using various methods for expansion and reduction. In the case of expansion, resizing can be performed using at least one data filling method, and in the case of reduction, resizing can be performed using at least one data removal method. At this time, in the case of resizing via an offset factor, new data or data of an existing image can be directly or modified and filled into the resizing area (expansion), and simple removal or removal through a series of processes can be applied to the resizing area (reduction) to be removed. When performing resizing via scale factor, in some cases (e.g., hierarchical encoding, etc.), expansion can perform resizing by applying upsampling, and reduction can perform resizing by applying downsampling. For example, in the case of expansion, at least one upsampling filter can be used, and in the case of reduction, at least one downsampling filter can be used, and the filters applied horizontally and vertically can be the same, and the filters applied horizontally and vertically can be different. At this time, in the case of resizing via scale factor, rather than creating or removing new data in the resizing area, data of an existing image can be rearranged using a method such as interpolation, and the data processing method related to performing resizing can be distinguished by the filter used for the sampling. In addition, in some cases (e.g., similar to offset factor), expansion can perform resizing by using at least one data filling method, and reduction can perform resizing by using at least one data removing method. In the present invention, the data processing method when performing resizing via offset factor will be mainly described. Typically, one data processing method set in advance can be used for the area being resized, but as in the example described below, at least one data processing method can be used for the area being resized, and selection information about the data processing method can be generated. In the former case, it can mean that resizing is performed using a fixed data processing method, and in the latter case, it can mean that resizing is performed using an adaptive data processing method. In addition, a common data processing method may be applied to the entire area (TL, TC, TR, ..., BR of FIGS. 7a and 7b) added or deleted during resizing, or the data processing method may be applied to a portion of the area (e.g., each of TL to BR of FIGS. 7a and 7b or a combination of portions thereof) added or deleted during resizing. FIG. 8 is an exemplary diagram of a method for configuring an expanded area in an image resizing method according to one embodiment of the present invention. Referring to 8a, the image can be divided into TL, TC, TR, LC, C, RC, BL, BC, and BR regions for convenience of explanation, and can correspond to the upper left, upper right, left, center, right, lower left, lower, and lower right positions of the image, respectively. In the following, the case where the image is expanded in the lower + right direction is described, but it should be understood that the same can be applied to other directions. The areas added as the image expands can be configured in various ways, for example, they can be filled with random values ​​or by referencing some data from the image. Referring to 8b, an area (A0, A2) extending to arbitrary pixel values ​​can be filled. The arbitrary pixel values ​​can be determined using various methods. For example, any pixel value can be a single pixel belonging to a pixel value range that can be expressed in bit depth {for example, from 0 to 1 << (bit_depth) -1}. For example, it can be a minimum value, a maximum value, a median value of the pixel value range {for example, 1 << (bit_depth - 1), etc.} (where bit_depth is the bit depth). For example, any pixel value is a range of pixel values ​​belonging to the image {e.g., min P From max P Until. min P , max P is the minimum and maximum values ​​among the pixels belonging to the image. min P is greater than or equal to 0 and max P can be a single pixel belonging to {1 << (bit_depth) - less than or equal to 1}. For example, any pixel value can be the minimum value, maximum value, median value, mean (of at least two pixels), weighted sum, etc. of the pixel value range. For example, an arbitrary pixel value may be a value determined from a pixel value range belonging to a part of an image. For example, when configuring A0, some parts may be TR+RC+BR. In addition, some parts may have 3 × 9 of TR, RC, BR as the corresponding parts, or 1 × 9 (assuming the rightmost line) as the corresponding parts, and this may depend on the encoding / decoding settings. At this time, some parts may be units divided from a picture division unit. Specifically, the arbitrary pixel value may be a minimum value, a maximum value, a median value, an average (of at least two pixels), a weighted sum, etc. of the pixel value range. Referring back to 8b, the area A1 added according to the image expansion can be filled using pattern information generated using multiple pixel values ​​(for example, assuming that using multiple pixels is a pattern. It does not necessarily have to follow a certain rule). At this time, the pattern information can be defined according to the encoding / decoding settings or related information can be generated, and the expanded area can be filled using at least one pattern information. Referring to 8c, an area added according to image expansion can be configured by referencing pixels of a part of an area belonging to the image. Specifically, the area added can be configured by copying or padding pixels of an area adjacent to the area to be added (hereinafter, referred to as reference pixels). At this time, the pixels of an area adjacent to the area to be added can be pixels before encoding or pixels after encoding (or decoding). For example, when performing resizing in a stage before encoding, the reference pixels can mean pixels of an input image, and when performing resizing in a stage of generating intra-screen prediction reference pixels, a stage of generating reference images, a stage of filtering, etc., the reference pixels can mean pixels of a restored image. In this example, it is assumed that the pixels closest to the area to be added are used, but it is not limited thereto. An area (A0) extending in the left or right direction related to horizontal resizing of an image can be configured by padding (Z0) the peripheral pixels adjacent to the area being extended (A0) in the horizontal direction, and an area (A1) extending in the upper or lower direction related to vertical resizing of an image can be configured by padding (Z1) the peripheral pixels adjacent to the area being extended (A1) in the vertical direction. In addition, an area (A2) extending in the lower right direction can be configured by padding (Z2) the peripheral pixels adjacent to the area being extended (A2) in the diagonal direction. Referring to 8d, an extended area (B'0 to B'2) can be configured by referencing data (B0 to B2) of some areas belonging to the image. In 8d, unlike 8c, it can be distinguished in that an area that is not adjacent to the extended area can be referenced. For example, if there is an area with a high correlation with the area being expanded within the image, the expanded area can be filled by referring to the pixels of the area with a high correlation. At this time, the location information, area size information, etc. of the area with a high correlation can be generated. Alternatively, if there is an area with a high correlation through the characteristics, type, etc. of the image, and the location information, size information, etc. of the area with a high correlation can be implicitly confirmed (for example, in the case of a 360-degree image), the data of the area can be filled in the expanded area. At this time, the location information, area size information, etc. of the area can be omitted. For example, in the case of an area (B'2) that extends in the left or right direction related to horizontal resizing of an image, the extended area can be filled by referring to pixels in an area (B2) opposite to the extended area in the left or right direction related to horizontal resizing. For example, in the case of an area (B'1) that extends in the upper or lower direction related to vertical resizing of an image, the extended area can be filled by referring to pixels in an area (B1) opposite to the extended area in the upper or right direction related to vertical resizing. For example, for an area (B'0) that is expanded by resizing part of the image (in the diagonal direction based on the center of the image in this example), the expanded area can be filled by referring to pixels in an area (B0, TL) opposite to the expanded area. In the above example, the case where continuity exists at both ends of the image and data of an area that is symmetrical to the resizing direction is acquired has been described, but it is not limited to this and it may also be possible to acquire data from other areas (TL ~ BR). When filling in data of a part of an image in an extended area, the data of the area can be copied as is or the data of the area can be filled after performing a conversion process based on the characteristics, type, etc. of the image. In this case, copying as is can mean using the pixel values ​​of the area as is, and performing a conversion process can mean not using the pixel values ​​of the area as is. In other words, at least one pixel value of the area can be changed through the conversion process to be filled in the extended area, or the acquisition positions of some pixels can be different by at least one. In other words, instead of using data of A×B of the area to fill in the extended area A×B, data of C×D can be used. In other words, at least one motion vector applied to the pixels to be filled can be different. The above example can be an example that occurs when filling in an extended area using data of another surface when a 360-degree image is composed of multiple surfaces according to the projection format. The data processing method for filling in an extended area by adjusting the size of the image is not limited to the above example, and may be improved and changed, or an additional data processing method may be used. Depending on the encoding / decoding settings, a plurality of candidates for data processing methods can be supported, and selection information for a data processing method among the plurality of candidates can be generated and included in the bitstream. For example, one data processing method can be selected from a method of filling using preset pixel values, a method of filling by copying peripheral pixels, a method of filling by copying a portion of an image, a method of filling by transforming a portion of an image, etc., and selection information for this can be generated. In addition, a data processing method can be implicitly determined. For example, a data processing method applied to the entire area (TL to BR in FIG. 7a in this example) expanded by resizing the image may be one of a method of filling using preset pixel values, a method of filling by copying peripheral pixels, a method of filling by copying a portion of the image, a method of filling by transforming a portion of the image, and other methods, and selection information for this may be generated. In addition, one preset data processing method applied to the entire area may be determined. Alternatively, the data processing method applied to an area expanded by resizing the image (in this example, each of the areas TL to BR in 7a of FIG. 7 or two or more areas therebetween) may be one of a method of filling using preset pixel values, a method of filling by copying peripheral pixels, a method of filling by copying a portion of the image, a method of filling by transforming a portion of the image, and other methods, and selection information for this may be generated. In addition, one preset data processing method applied to at least one area may be determined. FIG. 9 is an exemplary diagram of a method for configuring an area to be deleted and an area to be created according to image size reduction in an image size adjustment method according to one embodiment of the present invention. Areas that are deleted during the image reduction process may be removed not only by simply removing them, but also after going through a series of utilization processes. Referring to 9a, during the image reduction process, some areas (A0, A1, A2) can be simply removed without any additional utilization process. At this time, the image (A) can be subdivided and referred to as TL~BR, similar to Fig. 8a. Referring to 9b, some areas (A0 to A2) may be removed, but may be utilized as reference information when encoding / decoding the image (A). For example, some areas (A0 to A2) that are deleted may be utilized in the restoration process or correction process of some areas of the image (A) that is generated by reduction. The restoration or correction process may use a weighted sum, average, etc. of the two areas (the area to be deleted and the area to be generated). In addition, the restoration or correction process may be a process that can be applied when the two areas are highly correlated. For example, an area (B'2) that is deleted due to reduction in the left or right direction related to horizontal resizing of an image can be removed from memory after being used to restore or correct pixels in an area (B2, LC) opposite to the area that is reduced in the left or right direction related to horizontal resizing. For example, an area (B'1) deleted in the upper or lower direction related to vertical resizing of an image can be removed from memory after being used in the decoding / decoding process (restoration or correction process) of an area (B1, TR) opposite to the area being reduced in the upper or lower direction related to vertical resizing. For example, an area (B'0) that is reduced by resizing part of an image (in the diagonal direction based on the center of the image in this example) can be removed from memory after being used in the decoding / decoding process (such as restoration or correction process) of an area (B0, TL) opposite to the reduced area. In the above example, the description was given of a case where continuity exists at both ends of the image and data restoration or correction of an area in a symmetrical position relative to the resizing direction is used, but it is not limited thereto, and it may be removed from memory after being used for data restoration or correction of an area other than a symmetrical position (TL to BR). The data processing method for removing the reduced area of ​​the present invention is not limited to the above example, and the same may be improved and modified, or additional data processing methods may be used. Depending on the encoding / decoding settings, a candidate group for multiple data processing methods can be supported, and selection information for these can be generated and included in the bitstream. For example, one data processing method can be selected from a method of simply removing the resized area, a method of using the resized area in a series of processes and then removing it, and selection information for this can be generated. In addition, a data processing method can be implicitly determined. For example, the data processing method applied to the entire region (TL to BR in 7b of FIG. 7 in this example) that is deleted as the image is scaled down may be one of a simple removal method, a method of removing after being used in a series of processes, and other methods, and selection information for this may be generated. In addition, the data processing method may be implicitly determined. Alternatively, the data processing method applied to individual areas (TL to BR in FIG. 7b, in this example) that are reduced by resizing the image may be one of a simple removal method, a method of removing after using in a series of processes, or another method, and selection information for this may be generated. In addition, the data processing method may be implicitly determined. In the above example, the case of performing resizing according to a resizing operation (expanding, reducing) was described, but in some cases, it may be an example that can be applied when performing a resizing operation (expanding in this example) and then performing a resizing operation (reducing in this example), which is the reverse process of that. For example, a method is selected to fill an expanded area using some data of the image, and in the reverse process, a method is selected to remove the reduced area after using some data of the image for restoration or correction. Or, a method is selected to fill an expanded area using copies of peripheral pixels, and in the reverse process, a method is selected to simply remove the reduced area. In other words, the data processing method in the reverse process can be determined based on the data processing method selected in the image resizing process. Unlike the above example, the data processing method of the image resizing process and its reverse process may have an independent relationship. That is, the data processing method in the reverse process may be selected regardless of the data processing method selected in the image resizing process. For example, a method may be selected to fill the expanded area with some data of the image, and a method may be selected to simply remove the reduced area in the reverse process. In the present invention, the data processing method in the image resizing process can be implicitly determined according to the encoding / decoding settings, and the data processing method in the reverse process can be implicitly determined according to the encoding / decoding settings. Alternatively, the data processing method in the image resizing process can be explicitly generated, and the data processing method in the reverse process can be explicitly generated. Alternatively, the data processing method in the image resizing process can be explicitly generated, and the data processing method in the reverse process can be implicitly determined based on the data processing method. The following shows an example of performing image resizing in a sub / decoding device according to an embodiment of the present invention. In the examples described below, the resizing process will be exemplified as expansion, and the resizing reverse process as reduction. In addition, the difference between the “image before resizing” and the “image after resizing” may refer to the size of the image, and some of the resizing-related information may be explicitly generated or some of the information may be implicitly determined depending on the sub / decoding settings. In addition, the resizing-related information may include information on the resizing process and the resizing reverse process. As a first example, a resizing process can be performed on an input image before encoding begins. After resizing is performed using resizing information (e.g., resizing operation, resizing direction, resizing value, data processing method, etc.; the data processing method is used in the resizing process), the image after resizing can be encoded. After encoding is completed, it can be stored in memory, and the image encoding data (meaning the image after resizing in this example) can be included in a bitstream and transmitted. A resizing process can be performed before starting decoding. After resizing is performed using resizing information (e.g., resizing operation, resizing direction, resizing value, etc.), the image decoding data after resizing can be parsed and decoded. After decoding is completed, it can be stored in memory, and a resizing reverse process (using a data processing method, etc. in this example, which is used in the resizing reverse process) can be performed to change the output image to the image before resizing. As a second example, a resizing process for a reference image can be performed before encoding starts. After resizing is performed using resizing information (e.g., resizing operation, resizing direction, resizing value, data processing method, etc.; the data processing method is used in the resizing process), the image after resizing (the reference image after resizing in this example) can be stored in memory, and the image can be encoded using this. After encoding is completed, the image encoding data (meaning encoded using the reference image in this example) can be included in a bitstream and transmitted. In addition, the encoded image can perform a resizing process as in the above process when it is stored in memory as a reference image. A resizing process for a reference image can be performed before starting decoding. Using resizing information (e.g., resizing operation, resizing direction, resizing value, data processing method, etc.; the data processing method is used in the resizing process), a resized image (a resized reference image in this example) can be stored in memory, and image decoding data (the same as that encoded using the reference image in the encoder in this example) can be parsed and decoded. After decoding is completed, an output image can be generated, and if the decoded image is included as a reference image and stored in memory, a resizing process can be performed as in the above process. As a third example, after encoding is completed (more specifically, meaning encoding is completed excluding the filtering process), a resizing process can be performed on the image before filtering of the image (assumed to be a deblocking filter in this example) begins. After performing resizing using resizing information (e.g., resizing operation, resizing direction, resizing value, data processing method, etc. The data processing method is used in the resizing process), a resized image can be generated, and filtering can be applied to the resized image. After filtering is completed, a resizing reverse process can be performed to change it into an image before resizing. (Specifically, it means the completion of decoding excluding the filtering process) After the decoding is completed, a resizing process can be performed on the image before the filtering of the image starts. After performing resizing using resizing information (e.g., resizing operation, resizing direction, resizing value, data processing method, etc. The data processing method is used in the resizing process), the resized image can be generated, and filtering can be applied to the resized image. After the filtering is completed, a resizing reverse process can be performed to change it to the image before resizing. In some cases in the above examples (the first and third examples), the resizing process and the resizing reverse process may be performed, and in other cases (the second example), only the resizing process may be performed. In addition, in some cases (the second and third examples), the resizing process in the encoder and the decoder may be the same, and in some other cases (the first example), the resizing process in the encoder and the decoder may or may not be the same. In this case, the difference in the resizing process in the sub / decoder may be the resizing performing step. For example, in some cases (the encoder in this example), the resizing performing step may be included that considers the resizing of the image and the data processing of the resized region, and in some cases (the decoder in this example), the resizing performing step may be included that considers the resizing of the image. In this case, the data processing of the former may correspond to the data processing of the resizing inverse process. In addition, in some cases (example 3), the resizing process may be a process that is applied only at that stage, and the resized area may not be stored in the memory. For example, the area may be stored in a temporary memory for use in the filtering process, filtering may be performed, and the area may be removed through the resizing reverse process, and in this case, it can be said that there is no change in the size of the image due to the resizing. It is not limited to the above example, and variations to other examples may also be possible. Through the above resizing process, the size of the image may be changed, and accordingly, the coordinates of some pixels of the image may be changed through the resizing process, which may affect the operation of the picture segmentation unit. In the present invention, through the above process, segmentation in block units can be performed based on the image before resizing, or segmentation in block units can be performed based on the image after resizing. In addition, segmentation in some units (e.g., tiles, slices, etc.) can be performed based on the image before resizing, or segmentation in some units can be performed based on the image after resizing, and this can be determined according to the encoding / decoding settings. In the present invention, the description will be centered on the case where the picture segmentation unit operates based on the image after resizing (e.g., the image segmentation process after the resizing process), but other variations are also possible, and this will be described with respect to the above example in the multiple image settings described below. In the above process, the information generated will be recorded in the bitstream as at least one unit such as a sequence, picture, slice, or tile by the encoder, and the related information will be parsed from the bitstream. In addition, it can be included in the bitstream in the form of SEI or metadata. It may be common to perform encoding / decoding on the input image as is, but there may also be cases where encoding / decoding is performed by reconstructing the image. For example, image reconstruction may be performed for the purpose of increasing the encoding efficiency of the image, image reconstruction may be performed for the purpose of considering the network and user environment, and image reconstruction may be performed according to the type and characteristics of the image. In the present invention, the image reconstruction process can be performed alone or can perform the reverse process thereof. In the examples described below, the reconstruction process is explained with a focus on it, but the details of the reverse process can be derived from the reconstruction process. Figure 10 is an example diagram for image reconstruction according to one embodiment of the present invention. When 10a is the first input image, 10a to 10d are examples of applying a rotation including 0 degree to the image (for example, a candidate group can be generated by sampling 360 degrees into k sections. k can have values ​​such as 2, 4, 8, etc., and this example assumes 4) and 10e to 10h are examples of applying an inversion (or symmetry) based on 10a or based on 10b to 10d. Depending on the reconstruction of the image, the start position or scan order of the image may change, or the preset start position and scan order may be followed regardless of whether the image is reconstructed, which may be determined according to the encoding / decoding settings. In the embodiments described below, it is assumed that the preset start position (e.g., the upper left position of the image) and scan order (e.g., raster scan) are followed regardless of whether the image is reconstructed. The image encoding method and the decoding method according to one embodiment of the present invention may include the following image reconstruction steps. At this time, the image reconstruction process may include an image reconstruction instruction step, an image reconstruction type identification step, and an image reconstruction performance step. In addition, the image encoding device and the decoding device may be configured to include an image reconstruction instruction unit, an image reconstruction type identification unit, and an image reconstruction performance unit that implement the image reconstruction instruction step, the image reconstruction type identification step, and the image reconstruction performance step. In the case of encoding, related syntax elements may be generated, and in the case of decoding, related syntax elements may be parsed. In the image reconstruction instruction step, it is possible to determine whether to perform image reconstruction. For example, if a signal instructing image reconstruction (e.g., convert_enabled_flag) is confirmed, reconstruction can be performed, and if the signal instructing image reconstruction is not confirmed, reconstruction may not be performed or reconstruction may be performed by checking other sub / decoding information. In addition, even if a signal instructing image reconstruction is not provided, a signal instructing reconstruction may be implicitly activated or deactivated depending on sub / decoding settings (e.g., image characteristics, type, etc.), and when reconstruction is performed, reconstruction-related information may be generated accordingly or reconstruction-related information may be implicitly determined. When a signal instructing image reconstruction is provided, the signal is a signal for indicating whether to perform image reconstruction, and whether to perform image reconstruction can be determined according to the signal. For example, when a signal instructing image reconstruction (e.g., convert_enabled_flag) is confirmed and the signal is activated (e.g., convert_enabled_flag = 1), reconstruction can be performed, and when the signal is deactivated (e.g., convert_enabled_flag = 0), reconstruction may not be performed. In addition, if a signal instructing image reconstruction is not provided, reconstruction may not be performed, or whether the image is to be reconstructed may be confirmed by another signal. For example, reconstruction may be performed according to the characteristics, type, etc. of the image (e.g., 360-degree image), and reconstruction information may be explicitly generated or assigned as a preset value. The present invention is not limited to the above example, and variations to other examples may also be possible. In the image reconstruction type identification step, the image reconstruction type can be identified. The image reconstruction type can be defined by the method of performing the reconstruction, the reconstruction mode information, etc. The method of performing the reconstruction (e.g., convert_type_flag) can include rotation, inversion, etc., and the reconstruction mode information can include the mode (e.g., convert_mode) in the method of performing the reconstruction. In this case, the reconstruction-related information can be composed of the method of performing the reconstruction and the mode information. That is, it can be composed of at least one syntax element. At this time, the number of candidate groups of the mode information according to each method of performing the reconstruction can be the same or different. For example, in the case of rotation, candidates having a constant interval difference (90 degrees in this example) such as 10a to 10d can be included, and when 10a is rotated by 0 degrees, 10b to 10d can be examples of applying rotations of 90 degrees, 180 degrees, and 270 degrees, respectively (the angle is measured clockwise in this example). For example, in the case of inversion, candidates such as 10a, 10e, and 10f can be included, and when 10a is set to no inversion, 10e and 10f can be examples of left-right inversion and up-down inversion, respectively. The above example describes the case of setting for rotation with a certain interval and setting for some inversion, but it is only an example for image reconstruction and is not limited to the above case and can include examples such as other interval differences, other inversion operations, etc., which can be determined according to the encoding / decoding settings. Alternatively, it may include integrated information (e.g., convert_com_flag) generated by mixing the method of performing the reconstruction and the mode information accordingly. In this case, the reconstruction-related information may be composed of information in which the method of performing the reconstruction and the mode information are mixed. For example, the integrated information may include candidates such as 10a to 10f, which may be examples of applying 0 degree rotation, 90 degree rotation, 180 degree rotation, 270 degree rotation, left-right flip, and up-down flip based on 10a. Alternatively, the integrated information may include candidates such as 10a to 10h, which may be examples of applying 0 degree rotation, 90 degree rotation, 180 degree rotation, 270 degree rotation, left-right flip, up-down flip, 90 degree rotation followed by left-right flip (or left-right flip followed by 90 degree rotation), 90 degree rotation followed by up-down flip (or up-down flip followed by 90 degree rotation) based on 10a, or examples of applying 0 degree rotation, 90 degree rotation, 180 degree rotation, 270 degree rotation, left-right flip, 180 degree rotation followed by left-right flip (left-right flip followed by 180 degree rotation), 90 degree rotation followed by left-right flip (left-right flip followed by 90 degree rotation), 270 degree rotation followed by left-right flip (left-right flip followed by 270 degree rotation). The above candidate group may be configured to include a mode in which rotation is applied, a mode in which inversion is applied, and a mode in which rotation and inversion are mixedly applied. The mixed-configured mode may simply include mode information in a method of performing reconstruction, and may include a mode generated by mixing mode information in each method. At this time, it may include a mode generated by mixing at least one mode of some methods (e.g., rotation) and at least one mode of some methods (e.g., inversion), and the above example includes a case in which one mode of some methods and a plurality of modes of some methods are mixed and generated (in this example, 90 degree rotation + multiple inversions / left-right inversions + multiple rotations). The mixed-configured information may be configured to include a case in which reconstruction is not applied {10a in this example} as a candidate group, and may include a case in which reconstruction is not applied as a first candidate group (for example, 0 is assigned as an index). Alternatively, it may include mode information according to a method for performing a preset reconstruction. In this case, the reconstruction-related information may be composed of mode information according to a method for performing a preset reconstruction. That is, information on a method for performing reconstruction may be omitted and may be composed of a single syntactic element related to the mode information. For example, it can be composed of candidates such as 10a to 10d for rotation. Or, it can be composed of candidates such as 10a, 10e, 10f for inversion. The size of the image before and after the image reconstruction process may be the same or at least one length may be different, which may be determined according to the encoding / decoding settings. The image reconstruction process may be a process of performing rearrangement of pixels in the image (in this example, the reverse process of image reconstruction performs the reverse process of pixel rearrangement. This can be derived inversely from the pixel rearrangement process), and the position of at least one pixel may be changed. The rearrangement of the pixels may be performed according to a rule based on image reconstruction type information. At this time, the pixel rearrangement process can be affected by the size and shape of the image (e.g., square or rectangular). Specifically, the width and height of the image before the reconstruction process and the width and height of the image after the reconstruction process can act as variables in the pixel rearrangement process. For example, at least one of the ratio information (e.g., the former / the latter or the latter / the former, etc.) among the ratio of the width of the image before the reconstruction process to the width of the image after the reconstruction process, the ratio of the width of the image before the reconstruction process to the height of the image after the reconstruction process, the ratio of the width of the image before the reconstruction process to the height of the image after the reconstruction process, can act as a variable in the pixel rearrangement process. In the above example, if the sizes of the images before and after the reconstruction process are the same, the ratio of the width and height of the image can act as a variable in the pixel rearrangement process. In addition, if the shape of the image is square, the ratio of the image length before the reconstruction process and the image length after the reconstruction process can act as a variable in the pixel rearrangement process. In the image reconstruction performance step, image reconstruction can be performed based on the identified reconstruction information. That is, image reconstruction can be performed based on information such as reconstruction type and reconstruction mode, and encoding / decoding can be performed based on the acquired reconstructed image. The following shows an example of performing image reconstruction in a encoding / decoding device according to one embodiment of the present invention. A reconstruction process can be performed on the input image before encoding begins. After performing reconstruction using reconstruction information (e.g., image reconstruction type, reconstruction mode, etc.), the reconstructed image can be encoded. After encoding is completed, it can be stored in memory, and the image encoding data can be included in the bitstream and transmitted. A reconstruction process can be performed before starting decryption. After reconstruction is performed using reconstruction information (e.g., image reconstruction type, reconstruction mode, etc.), the image decryption data can be parsed and decoded. After decryption is completed, it can be stored in memory, and the image can be output after performing a reconstruction reverse process to change it to an image before reconstruction. In the above process, the information generated will be recorded in the bitstream as at least one unit such as a sequence, picture, slice, or tile by the encoder, and the related information will be parsed from the bitstream. In addition, it can be included in the bitstream in the form of SEI or metadata. Table 1 shows examples of syntax elements related to segmentation during image setup. The examples described below will focus on the additional syntax elements. In addition, the syntax elements of the examples described below are not limited to any specific unit and may be syntax elements supported in various units such as sequences, pictures, slices, and tiles. Or, they may be syntax elements included in SEI, metadata, etc. In addition, the types of syntax elements supported in the examples described below, the order of syntax elements, conditions, etc. are limited only to this example and may be changed and determined according to the encoding / decoding settings. In Table 1, tile_header_enabled_flag means a syntax element for whether or not to support sub / decryption settings for tiles. When enabled (tile_header_enabled_flag = 1), sub / decryption settings can be had per tile, and when disabled (tile_header_enabled_flag = 0), sub / decryption settings cannot be had per tile and sub / decryption settings of a higher unit can be assigned. tile_coded_flag is a syntax element indicating whether a tile is encoded / decoded. When activated (tile_coded_flag = 1), encoding / decoding of the corresponding tile can be performed, and when deactivated (tile_coded_flag = 0), encoding / decoding cannot be performed. Here, not performing encoding may mean not generating encoded data for the corresponding tile (in this example, it is assumed that the corresponding area is processed by a preset rule, etc. It can be applied to a meaningless area in some projection formats of a 360-degree image). Not performing decoding may mean not parsing the decoded data for the corresponding tile any further (in this example, it is assumed that the corresponding area is processed by a preset rule, etc.). In addition, not parsing the decoded data any further may mean that encoded data does not exist in the corresponding unit and thus is not parsed any further, but may also mean that even if encoded data exists, it is not parsed any further due to the flag. Header information per tile may be supported depending on whether tile encoding / decoding is performed. Although the above example has been explained with a focus on tiles, it is not limited to tiles, and may be an example that can be applied to other division units in the present invention. In addition, it is not limited to the above case as an example of the division setting of tiles, and modifications to other examples may also be possible. Table 2 shows examples of syntactic elements related to reconstruction during image setup. Referring to Table 2, convert_enabled_flag means a syntax element for whether reconstruction is performed. When enabled (convert_enabled_flag = 1), it means to decode / encode the reconstructed image, and additional reconstruction-related information can be checked. When disabled (convert_enabled_flag = 0), it means to decode / encode the existing image. convert_type_flag indicates the mixed information about the method of performing reconstruction and the mode information. It can be determined as one of multiple candidates for the method of applying rotation, the method of applying inversion, and the method of applying a mixture of rotation and inversion. Table 3 shows examples of syntax elements related to resizing during image setup. Referring to Table 3, pic_width_in_samples and pic_height_in_samples represent syntax elements related to the width and height of the image, and the size of the image can be checked with the syntax elements. img_resizing_enabled_flag is a syntax element for whether or not to resize the image. When enabled (img_resizing_enabled_flag = 1), it means to decode / encode the image after resizing, and you can check additional resizing-related information. When disabled (img_resizing_enabled_flag = 0), it means to decode / encode the existing image. It can also be a syntax element for resizing for intra-screen prediction. resizing_met_flag is a syntax element for the resizing method. It can be determined as one of the candidates, such as resizing via scale factor (resizing_met_flag = 0), resizing via offset factor (resizing_met_flag = 1), or other resizing methods. resizing_mov_flag is a syntax element for the resizing operation. For example, it can be determined as either expanding or shrinking. width_scale and height_scale refer to scale factors related to horizontal and vertical resizing in resizing via scale factors. top_height_offset and bottom_height_offset refer to the upper and lower offset factors related to horizontal resizing during resizing using offset factors, and left_width_offset and right_width_offset refer to the left and right offset factors related to vertical resizing during resizing using offset factors. The size of the image can be updated after resizing using the above resizing-related information and image size information. resizing_type_flag is a syntax element for how to process data in the area being resized. Depending on the resizing method and resizing action, the number of candidates for the data processing method may be the same or different. The image setting process applied to the aforementioned image encoding / decoding device may be performed individually or may be performed by mixing multiple image setting processes. In the example described below, a description will be given of a case where multiple image setting processes are performed by mixing multiple processes. FIG. 11 is an exemplary diagram showing images before and after an image setting process according to an embodiment of the present invention. Specifically, 11a is an example before performing image reconstruction on a segmented image (e.g., a projected image in 360-degree image encoding), and 11b is an example after performing image reconstruction on a segmented image (e.g., a packaged image in 360-degree image encoding). In other words, 11a can be understood as an exemplary diagram before performing an image setting process, and 11b can be understood as an exemplary diagram after performing an image setting process. In this example, the image setup process will cover the cases of image segmentation (assumed to be tiles in this example) and image reconstruction. In the examples described below, the case where image reconstruction is performed after image segmentation is performed is described, but depending on the encoding / decoding settings, there may be cases where image segmentation is performed after image reconstruction is performed, and variations to other cases may also be possible. In addition, the image reconstruction process described above (including the reverse process) may be applied in the same or similar way as the reconstruction process of the segmentation unit within the image in this embodiment. Image reconstruction may or may not be performed on all segmentation units in the image, or may be performed on some segmentation units. Accordingly, segmentation units before reconstruction (e.g., some of P0 to P5) may or may not be the same as segmentation units after reconstruction (e.g., some of S0 to S5). Various cases of performing image reconstruction are described through examples described below. In addition, for convenience of explanation, it is assumed that the unit of the image is a picture, the unit of the segmented image is a tile, and the segmentation unit is a square shape. For example, whether to perform image reconstruction can be determined in some units (e.g., sps_convert_enabled_flag or SEI or metadata, etc.). Alternatively, whether to perform image reconstruction can be determined in some units (e.g., pps_convert_enabled_flag), and this can be possible when it first occurs in the unit (a picture in this example) or when it is activated in a higher unit (e.g., sps_convert_enabled_flag = 1). Alternatively, whether to perform image reconstruction can be determined in some units (e.g., tile_convert_flag[i], where i is a segmentation unit index), and this can be possible when it first occurs in the unit (a tile in this example) or when it is activated in a higher unit (e.g., pps_convert_enabled_flag = 1). In addition, whether to perform reconstruction of some of the images can be implicitly determined according to encoding / decoding settings, and thus, related information can be omitted. For example, whether to perform reconstruction of a segmentation unit within an image may be determined based on a signal instructing reconstruction of the image (e.g., pps_convert_enabled_flag). Specifically, whether to perform reconstruction of all segmentation units within an image may be determined based on the signal. At this time, a signal instructing reconstruction of one image may be generated in the image. For example, whether to perform reconstruction of a segmentation unit within an image may be determined based on a signal instructing reconstruction of an image (e.g., tile_convert_flag[i]). Specifically, whether to perform reconstruction of some segmentation units within an image may be determined based on the signal. At this time, at least one signal instructing reconstruction of an image (e.g., generated as many times as the number of segmentation units) may be generated. For example, whether to perform image reconstruction may be determined based on a signal instructing image reconstruction (e.g., pps_convert_enabled_flag), and whether to perform reconstruction of a segmentation unit within an image may be determined based on a signal instructing image reconstruction (e.g., tile_convert_flag[i]). Specifically, when some signals are activated (e.g., pps_convert_enabled_flag = 1), some signals (e.g., tile_convert_flag[i]) may be additionally checked, and whether to perform reconstruction of some segmentation units within an image may be determined based on the signal (tile_convert_flag[i] in this example). At this time, signals instructing reconstruction of multiple images may be generated. Image reconstruction-related information may be generated when a signal instructing image reconstruction is activated. The following examples describe cases of various image reconstruction-related information. For example, reconstruction information applied to an image may occur. Specifically, a single reconstruction information may be used as reconstruction information for all segmentation units in the image. For example, reconstruction information applied to a segmentation unit within an image may occur. Specifically, at least one reconstruction information may be used as reconstruction information for some segmentation units within an image. That is, one reconstruction information may be used as reconstruction information for one segmentation unit, or one reconstruction information may be used as reconstruction information for multiple segmentation units. The examples described below can be explained in combination with examples that perform image reconstruction. For example, when a signal instructing image reconstruction (e.g., pps_convert_enabled_flag) is activated, reconstruction information commonly applied to segmentation units within the image may be generated. Or, when a signal instructing image reconstruction (e.g., pps_convert_enabled_flag) is activated, reconstruction information individually applied to segmentation units within the image may be generated. Or, when a signal instructing image reconstruction (e.g., tile_convert_flag[i]) is activated, reconstruction information individually applied to segmentation units within the image may be generated. Or, when a signal instructing image reconstruction (e.g., tile_convert_flag[i]) is activated, reconstruction information commonly applied to segmentation units within the image may be generated. In the case of the above reconstruction information, implicit or explicit processing can be performed depending on the encoding / decoding settings. In the case of implicit processing, reconstruction information can be assigned to preset values ​​depending on the characteristics and type of the image. P0 to P5 of 11a can correspond to S0 to S5 of 11b, and a reconstruction process can be performed on the partition unit. For example, P0 can be assigned to SO without reconstruction, P1 can be assigned to S1 by applying a 90-degree rotation, P2 can be assigned to S2 by applying a 180-degree rotation, P3 can be assigned to S3 by applying a left-right inversion, P4 can be assigned to S4 by applying a 90-degree rotation and then a left-right inversion, and P5 can be assigned to S5 by applying a 180-degree rotation and then a left-right inversion. However, it is not limited to the above example, and various examples of modifications may also be possible. As in the above example, it is possible to perform reconstruction without performing reconstruction on the image segmentation unit, or to perform at least one of reconstruction methods among reconstruction applying rotation, reconstruction applying inversion, and reconstruction applying a mixture of rotation and inversion. When image reconstruction is applied to a segmentation unit, an additional reconstruction process such as segmentation unit rearrangement can be performed. That is, the image reconstruction process of the present invention can be configured to include rearrangement of segmentation units within an image in addition to performing rearrangement of pixels within an image, and can be expressed by some syntactic elements (e.g., part_top, part_left, part_width, part_height, etc.) as shown in Table 4. This means that the image segmentation and image reconstruction processes can be understood as being mixed. The above description can be a possible example when an image is divided into multiple units. P0 to P5 of 11a may correspond to S0 to S5 of 11b, and a reconstruction process may be performed on the partition unit. For example, P0 may be assigned to S0 without performing reconstruction, P1 may be assigned to S2 without performing reconstruction, P2 may be assigned to S1 by applying a 90-degree rotation, P3 may be assigned to S4 by applying a left-right inversion, P4 may be assigned to S5 by applying a 90-degree rotation and then a left-right inversion, and P5 may be assigned to S3 by applying a left-right inversion and then a 180-degree rotation, and the present invention is not limited thereto, and various examples of modifications may also be possible. Additionally, P_Width and P_Height of Fig. 7 may correspond to P_Width and P_Height of Fig. 11, and P'_Width and P'_Height of Fig. 7 may correspond to P'_Width and P'_Height of Fig. 11. In Fig. 7, the image size after resizing is P'_Width × P'_Height, which can be expressed as (P_Width + Exp_L + Exp_R) × (P_Height + Exp_T + Exp_B), and in Fig. 11, the image size after resizing is P'_Width × P'_Height, which can be expressed as (P_Width + Var0_L + Var1_L + Var2_L + Var0_R + Var1_R + Var2_R) × (P_Height + Var0_T + Var1_T + Var0_B + Var1_B), or (Sub_P0_Width + Sub_P1_Width + Sub_P2_Width + Var0_L + Var1_L + Var2_L + Var0_R + Var1_R + Var2_R) × (Sub_P0_Height + Sub_P1_Height + Var0_T + Var1_T + Var0_B + It can be expressed as Var1_B). As in the above example, image reconstruction can perform pixel rearrangement within a segmentation unit of an image, can perform rearrangement of segmentation units within an image, and can perform rearrangement of pixels within a segmentation unit of an image as well as rearrangement of segmentation units within an image. At this time, rearrangement of pixels within a segmentation unit can be performed after rearrangement of pixels within a segmentation unit, or rearrangement of pixels within a segmentation unit can be performed after rearrangement of pixels within a segmentation unit is performed. The rearrangement of the segmentation units within the image may be determined based on a signal instructing the reconstruction of the image. Alternatively, a signal for the rearrangement of the segmentation units within the image may be generated. Specifically, the signal may be generated when the signal instructing the reconstruction of the image is activated. Alternatively, implicit or explicit processing may be performed based on the encoding / decoding settings. In the case of implicit processing, it may be determined based on the characteristics, type, etc. of the image. In addition, information on the rearrangement of segmentation units within an image can be implicitly or explicitly processed according to encoding / decoding settings, and can be determined according to the characteristics and type of the image. In other words, each segmentation unit can be arranged according to the arrangement information of the preset segmentation units. The following shows an example of performing reconstruction of a segmentation unit within an image in a encoding / decoding device according to one embodiment of the present invention. Before encoding begins, a segmentation process can be performed on the input image using segmentation information. A reconstruction process can be performed on the segmentation unit using reconstruction information, and the reconstructed image can be encoded on the segmentation unit. After encoding is completed, it can be stored in memory, and the image encoding data can be included in the bitstream and transmitted. Before starting decoding, the segmentation process can be performed using segmentation information. The reconstruction process can be performed using reconstruction information for each segmentation unit, and the image decoding data can be parsed and decoded by the segmentation unit where reconstruction was performed. After decoding is completed, it can be stored in memory, and after performing the reconstruction reverse process for each segmentation unit, the segmentation units can be merged into one to output the image. Fig. 12 is an example diagram of size adjustment for each segmentation unit in an image according to one embodiment of the present invention. P0 to P5 of Fig. 12 correspond to P0 to P5 of Fig. 11, and S0 to S5 of Fig. 12 correspond to S0 to S5 of Fig. 11. In the examples described below, the explanation is centered on the case where image resizing is performed after image segmentation, but it is also possible to perform image segmentation after image resizing depending on the encoding / decoding settings, and transformations to other cases are also possible. In addition, the image resizing process described above (including the reverse process) can be applied in the same or similar way as the resizing process of the segmentation unit within the image in this embodiment. For example, TL ~ BR of FIG. 7 may correspond to TL ~ BR of the division unit SX (S0 ~ S5) of FIG. 12, S0 and S1 of FIG. 7 may correspond to PX and SX of FIG. 12, P_Width and P_Height of FIG. 7 may correspond to Sub_PX_Width and Sub_PX_Height of FIG. 12, P'_Width and P'_Height of FIG. 7 may correspond to Sub_SX_Width and Sub_SX_Height of FIG. 12, Exp_L, Exp_R, Exp_T, Exp_B of FIG. 7 may correspond to VarX_L, VarX_R, VarX_T, VarX_B of FIG. 12, and other factors may also correspond. The process of adjusting the size of the segmentation units in the image in FIGS. 12a to 12f can be distinguished from the process of adjusting the size of the image in FIGS. 7a and 7b in that there can be settings for enlarging or reducing the size of the image in proportion to the number of segmentation units. In addition, there can be a difference in that there are settings that are commonly applied to the segmentation units in the image or settings that are individually applied to the segmentation units in the image. In the examples described below, cases of resizing in various cases will be described, and the resizing process can be performed in consideration of the above. In the present invention, image resizing may or may not be performed on all segmentation units in the image, and may be performed on some segmentation units. Various cases of image resizing will be described through examples described below. In addition, for convenience of explanation, the resizing operation is described assuming that the method of performing expansion and resizing is an offset factor, the resizing direction is an up, down, left, and right direction, the resizing direction is a setting that operates by resizing information, the unit of the image is a picture, and the unit of the segmented image is a tile. For example, whether to perform image resizing can be determined in some units (e.g., sps_img_resizing_enabled_flag, or SEI or metadata, etc.). Or, whether to perform image resizing can be determined in some units (e.g., pps_img_resizing_enabled_flag), and this can be possible when it first occurs in the unit (a picture in this example) or when it is enabled in a higher unit (e.g., sps_img_resizing_enabled_flag = 1). Or, whether to perform image resizing can be determined in some units (e.g., tile_resizing_flag[i], where i is a segmentation unit index), and this can be possible when it first occurs in the unit (a tile in this example) or when it is enabled in a higher unit. In addition, whether to perform image resizing can be implicitly determined according to encoding / decoding settings, and thus, related information can be omitted. For example, whether to perform resizing of a segmentation unit within an image may be determined based on a signal instructing resizing of an image (e.g., pps_img_resizing_enabled_flag). Specifically, whether to perform resizing of all segmentation units within an image may be determined based on the signal. At this time, a signal instructing resizing of one image may be generated. For example, whether to perform resizing of a segmentation unit within an image may be determined based on a signal instructing resizing of an image (e.g., tile_resizing_flag[i]). Specifically, whether to perform resizing of some segmentation units within an image may be determined based on the signal. At this time, at least one signal instructing resizing of an image (e.g., generated as many times as the number of segmentation units) may be generated. For example, whether to perform image resizing may be determined based on a signal instructing image resizing (e.g., pps_img_resizing_enabled_flag), and whether to perform resizing of a segmentation unit within the image may be determined based on a signal instructing image resizing (e.g., tile_resizing_flag[i]). Specifically, when some signals are activated (e.g., pps_img_resizing_enabled_flag = 1), additionally some signals (e.g., tile_resizing_flag[i]) may be checked, and whether to perform resizing of some segmentation units within the image may be determined based on the signal (tile_resizing_flag[i] in this example). At this time, signals instructing resizing of multiple images may be generated. When a signal indicating image resizing is activated, image resizing related information may be generated. The following examples describe cases regarding various image resizing related information. For example, resizing information applied to an image may occur. Specifically, one resizing information or a set of resizing information may be used as resizing information for all segmentation units in the image. For example, one resizing information commonly applied to the up, down, left, and right directions of the segmentation units in the image (or, a resizing value applied to all resizing directions supported or allowed by the segmentation unit; in this example, one piece of information) or one resizing information set applied to each of the up, down, left, and right directions (or, as many as the number of resizing directions supported or allowed by the segmentation unit; in this example, up to four pieces of information) may occur. For example, resizing information applied to a segmentation unit within an image may be generated. Specifically, at least one resizing information or a set of resizing information may be used as resizing information of some segmentation units within an image. That is, one resizing information or a set of resizing information may be used as resizing information of one segmentation unit or may be used as resizing information of a plurality of segmentation units. For example, one resizing information commonly applied to the upper, lower, left, and right directions of one segmentation unit within an image or one resizing information set applied respectively to the upper, lower, left, and right directions may be generated. Alternatively, one resizing information commonly applied to the upper, lower, left, and right directions of a plurality of segmentation units within an image or one resizing information set applied respectively to the upper, lower, left, and right directions may be generated. The configuration of a resizing set means resizing value information for at least one resizing direction. In summary, resizing information that is commonly applied to the segmentation units within an image may occur. Or, resizing information that is individually applied to the segmentation units within an image may occur. The example described below can be explained through combination with an example of performing image resizing. For example, when a signal instructing resizing of an image (e.g., pps_img_resizing_enabled_flag) is activated, resizing information commonly applied to segmentation units within an image may be generated. Or, when a signal instructing resizing of an image (e.g., pps_img_resizing_enabled_flag) is activated, resizing information individually applied to segmentation units within an image may be generated. Or, when a signal instructing resizing of an image (e.g., tile_resizing_flag[i]) is activated, resizing information individually applied to segmentation units within an image may be generated. Or, when a signal instructing resizing of an image (e.g., tile_resizing_flag[i]) is activated, resizing information commonly applied to segmentation units within an image may be generated. The image resizing direction, resizing information, etc. can be processed implicitly or explicitly depending on the encoding / decoding settings. In the implicit case, the resizing information can be assigned as a preset value depending on the characteristics and type of the image. In the resizing process of the present invention described above, the resizing direction is at least one of the up, down, left, and right directions, and it has been explained that the resizing direction and resizing information can be processed explicitly or implicitly. That is, some directions can be implicitly predetermined with a resizing value (including 0, i.e., no adjustment), and some directions can be explicitly assigned with a resizing value (including 0, i.e., no adjustment). Even in the segmentation unit within the image, the resize direction and the resize information can have settings that can be implicitly or explicitly processed, and these can be applied to the segmentation unit within the image. For example, a setting that is applied to one segmentation unit within the image (which occurs as many times as the number of segmentation units in this example) can occur, or a setting that is applied to multiple segmentation units within the image can occur, or a setting that is applied to all segmentation units within the image (which occurs as one setting in this example) can occur, and at least one setting can occur in the image (for example, from one setting to as many settings as the number of segmentation units can occur). A single setting set can be defined by gathering the setting information that is applied to the segmentation units within the image. Figure 13 is an example diagram for a set of resizing or setting of segmentation units within an image. In detail, various examples of the resizing direction of the segmentation unit in the image and the implicit or explicit processing of the resizing information are presented. In the examples described below, for the convenience of explanation, implicit processing is explained assuming that the resizing value in some resizing directions is 0. In cases where the boundary of the segmentation unit matches the boundary of the image, such as in 13a (bold solid line in this example), explicit processing of resizing can be performed, and implicit processing can be performed when they do not match (thin solid line). For example, P0 can be resized in the upward and left directions (a2, a0), P1 in the upward direction (a2), P2 in the upward and right directions (a2, a1), P3 in the downward and left directions (a3, a0), P4 in the downward direction (a3), and P5 in the downward and right directions (a3, a1), but resizing in other directions may not be possible. As in 13b, some directions of the segmentation unit (up and down in this example) can be explicitly processed for resizing, and some directions of the segmentation unit (left and right in this example) can be explicitly processed (bold solid line in this example) when the boundary of the segmentation unit matches the boundary of the image, and implicitly processed (thin solid line in this example) when they do not match. For example, P0 can be resized in the up, down, and left directions (b2, b3, b0), P1 can be resized in the up and down directions (b2, b3), P2 can be resized in the up, down, and right directions (b2, b3, b1), P3 can be resized in the up, down, and left directions (b3, b4, b0), P4 can be resized in the up and down directions (b3, b4), and P5 can be resized in the up, down, and right directions (b3, b4, b1), and other directions may not be resized. As in 13c, some directions of the segmentation unit (left and right in this example) can be explicitly processed for resizing, and some directions of the segmentation unit (up and down in this example) can be explicitly processed when the boundary of the segmentation unit matches the boundary of the image (bold solid line in this example), and implicitly processed when they do not match (thin solid line in this example). For example, P0 can be resized in the up, left, and right directions (c4, c0, c1), P1 can be resized in the up, left, and right directions (c4, c1, c2), P2 can be resized in the up, left, and right directions (c4, c2, c3), P3 can be resized in the down, left, and right directions (c5, c0, c1), P4 can be resized in the down, left, and right directions (c5, c1, c2), and P5 can be resized in the down, left, and right directions (c5, c2, c3), and other directions may not be resized. As in the above example, settings related to image resizing can have various cases. Multiple sets of settings can be supported, so that setting set selection information can be explicitly generated, or a preset setting set can be implicitly determined based on encoding / decoding settings (e.g., image characteristics, type, etc.). Figure 14 is an example diagram showing the process of resizing an image and the process of resizing a segmentation unit within an image. Referring to Fig. 14, the image resizing process and the reverse process can be performed as e and f, and the resizing process and the reverse process of the segmentation unit within the image can be performed as d and g. That is, the resizing process can be performed on the image, and the resizing of the segmentation unit within the image can be performed, and the order of the resizing process may not be fixed. This means that multiple resizing processes can be possible. In summary, the image resizing process can be classified into image resizing (or image resizing before segmentation) and image resizing of the segmentation unit within the image (or image resizing after segmentation), and neither image resizing nor image resizing of the segmentation unit within the image can be performed, either one of the two can be performed, or both can be performed, which can be determined by the encoding / decoding settings (e.g., image characteristics, type, etc.). In the above example, when performing multiple resizing processes, the resizing of the image can be performed in at least one direction among the upper, lower, left, and right directions of the image, and the resizing of at least one segmentation unit among the segmentation units within the image can be performed, and at this time, the resizing can be performed in at least one direction among the upper, lower, left, and right directions of the segmentation unit for which resizing is performed. Referring to FIG. 14, the size of the image before resizing (A) can be defined as P_Width × P_Height, the size of the image after the first resize (or the image before the second resize, B) can be defined as P'_Width × P'_Height, and the size of the image after the second resize (or the image after the final resize, C) can be defined as P''_Width × P''_Height. The image before resizing (A) means an image without any resizing, the image after the first resize (B) means an image with some resizing performed, and the image after the second resize (C) means an image with all resizing performed. For example, the image (B) after the first resize may mean an image in which the resize of the segmentation unit within the image is performed as in FIGS. 13a to 13c, and the image (C) after the second resize may mean an image in which the resize is performed on the entire image (B) that was subjected to the first resize as in FIG. 7a, and the opposite case is also possible. The present invention is not limited to the above examples and various examples of modification may be possible. After the first resizing, in the size of the image (B), P'_Width can be obtained through P_Width and at least one resizing value in the left or right direction that can be resized horizontally, and P'_Height can be obtained through P_Height and at least one resizing value in the up or down direction that can be resized vertically. At this time, the resizing value may be a resizing value that occurs in a division unit. In the size of the image (C) after the second resizing, P''_Width can be obtained through P'_Width and at least one resizing value in the left or right direction that can be resized horizontally, and P''_Height can be obtained through P'_Height and at least one resizing value in the up or down direction that can be resized vertically. At this time, the resizing value may be a resizing value occurring in the image. In summary, the size of the image after resizing can be obtained through the size of the image before resizing and at least one resizing value. Information on the data processing method may occur in the area of ​​the image being resized. Various cases of data processing methods will be explained through examples described below, and the data processing method occurring in the resizing reverse process can be applied in the same or similar way as in the resizing process, and the data processing method in the resizing process and the resizing reverse process can be explained through various combinations of the cases described below. For example, a data processing method applied to an image may occur. Specifically, one data processing method or a set of data processing methods may be used as a data processing method for all segmentation units in the image (assuming that all segmentation units are resized in this example). For example, one data processing method commonly applied to the up, down, left, and right directions of the segmentation units in the image (or a data processing method applied to all resizing directions supported or allowed by the segmentation unit; in this example, one information) or one set of data processing methods applied to the up, down, left, and right directions respectively (or as many as the number of resizing directions supported or allowed by the segmentation unit; in this example, up to four information) may occur. For example, a data processing method applied to a segmentation unit within an image may occur. Specifically, at least one data processing method or a set of data processing methods may be used as a data processing method for some segmentation units (assumed to be resized segmentation units in this example) within an image. That is, one data processing method or a set of data processing methods may be used as a data processing method for one segmentation unit or may be used as a data processing method for multiple segmentation units. For example, one data processing method commonly applied to the up, down, left, and right directions of one segmentation unit within an image or one data processing method set applied respectively to the up, down, left, and right directions may occur. Alternatively, one data processing method commonly applied to the up, down, left, and right directions of multiple segmentation units within an image or one data processing method information set applied respectively to the up, down, left, and right directions may occur. The configuration of a set of data processing methods means a data processing method for at least one resizing direction. In summary, a data processing method commonly applied to the segmentation units in the image can be used. Or, a data processing method individually applied to the segmentation units in the image can be used. The data processing method can use a preset method. The preset data processing method can have at least one method, which corresponds to an implicit case, and explicit selection information on the data processing method can occur, which can be determined according to the encoding / decoding settings (e.g., the characteristics, type, etc. of the image). That is, a data processing method commonly applied to the segmentation units within an image can be used, a preset method can be used, or one of multiple data processing methods can be selected. Alternatively, a data processing method individually applied to the segmentation units within an image can be used, and a preset method can be used or one of multiple data processing methods can be selected depending on the segmentation unit. The examples below illustrate some cases involving resizing (in this example assumed to be expansion) of segmentation units within an image (in this example using some data from the image to fill the resized region). Some regions (TL to BR) of some units (for example, S0 to S5 of FIGS. 12A to 12F) can be resized using data of some regions (tl to br) of some units (P0 to P5 of FIGS. 12A to 12F). At this time, the some units may be the same (for example, S0 and P0) or not the same (for example, S0 and P1). That is, the regions (TL to BR) to be resized can be filled using some data (tl to br) of the corresponding division unit, and the regions to be resized can be filled using some data of a division unit different from the corresponding division unit. For example, the resized region (TL ~ BR) of the current partition unit can be resized using the tl ~ br data of the current partition unit. For example, TL of S0 can be filled using tl data of P0, RC of S1 can be filled using tr + rc + br data of P1, BL + BC of S2 can be filled using bl + bc + br data of P2, and TL + LC + BL of S3 can be filled using tl + lc + bl data of P3. For example, the resized region (TL ~ BR) of the current partition unit can be resized using tl ~ br data of the partition units spatially adjacent to the current partition unit. For example, TL + TC + TR of S4 can be filled using bl + bc + br data of P1 in the upper direction, BL + BC of S2 can be filled using tl + tc + tr data of P5 in the lower direction, LC + BL of S2 can be filled using tl + rc + bl data of P1 in the left direction, RC of S3 can be filled using tl + lc + bl data of P4 in the right direction, and BR of S0 can be filled using tl data of P4 in the lower-left direction. For example, the resized region (TL ~ BR) of the current segmentation unit can be resized using tl ~ br data of segmentation units that are not spatially adjacent to the current segmentation unit. For example, data of regions at both end boundaries (e.g., left and right, top and bottom, etc.) of the image can be acquired. The LC of S3 can be acquired using tr + rc + br data of S5, the RC of S2 can be acquired using tl + lc data of S0, the BC of S4 can be acquired using tc + tr data of S1, and the TC of S1 can be acquired using bc data of S4. Alternatively, data from a portion of the image (a region that is not spatially adjacent but is judged to have a high correlation with the region being resized) can be obtained. BC of S1 can be obtained using tl + lc + bl data of S3, RC of S3 can be obtained using tl + tc data of S1, and RC of S5 can be obtained using bc data of S0. Also, in some cases (in this example, some data of the image is removed by restoration or correction) regarding the resizing of the segmentation unit within the image (assumed to be reduced in this example) are as follows. Some regions (TL to BR) of some units (for example, S0 to S5 of FIGS. 12A to 12F) may be used in the restoration or correction process of some regions (tl to br) of some units (P0 to P5). At this time, the some units may be identical (for example, S0 and P0) or non-identical regions (for example, S0 and P2). That is, the region being resized may be used for restoring some data of the corresponding division unit and may be removed, and the region being resized may be used for restoring some data of a division unit different from the corresponding division unit and may be removed. A detailed example is omitted because it can be derived inversely from the expansion process. The above example may be applied when there is highly correlated data in the area being resized, and information on the location referenced for resizing may be explicitly generated or implicitly acquired according to preset rules, or the related information may be identified by mixing them. This may be applied when data is acquired from another area where continuity exists in encoding a 360-degree video. The following shows an example of performing size adjustment of a segmentation unit within an image in a encoding / decoding device according to one embodiment of the present invention. A segmentation process can be performed on the input image before encoding begins. A resizing process can be performed using resizing information for the segmentation unit, and the image can be encoded after resizing the segmentation unit. After encoding is completed, it can be stored in memory, and the image encoding data can be included in the bitstream and transmitted. Before starting decoding, the segmentation process can be performed using the segmentation information. The size adjustment information can be used for the segmentation unit to perform the size adjustment process, and the image decoding data can be parsed and decoded by the segmentation unit in which the size adjustment was performed. After the decoding is completed, it can be stored in memory, and after performing the size adjustment reverse process of the segmentation unit, the segmentation units can be merged into one to output the image. In other cases in the aforementioned video resizing process, changes may be applied as in the above example, and changes to other examples may also be possible without being limited thereto. In the above image setting process, a combination of image resizing and image reconstruction may be possible. Image reconstruction may be performed after image resizing is performed, or image resizing may be performed after image reconstruction is performed. In addition, a combination of image segmentation, image reconstruction, and image resizing may be possible. Image resizing and image reconstruction may be performed after image segmentation is performed, and the order of image settings is not fixed and can be changed, and this can be determined according to the sub / decoding settings. In this example, the image setting process is described as a case where image segmentation is performed, image reconstruction is performed, and image resizing is performed, but a different order is possible and a change to a different case may also be possible, depending on the sub / decoding settings. For example, it can proceed in the following order: split -> reconstruct, reconstruct -> split, split -> resize, resize -> split, resize -> reconstruct, reconstruct -> resize, split -> reconstruct -> resize, split -> resize -> reconstruct, resize -> split -> reconstruct, resize -> reconstruct, resize -> split, reconstruct -> split -> resize, reconstruct -> split -> resize, reconstruct -> resize -> split, and combinations with additional image settings are also possible. As described above, the image setting processes can be performed sequentially, but it is also possible to perform all or part of the setting processes simultaneously. In addition, some image setting processes can be performed in multiple steps depending on the encoding / decoding settings (e.g., image characteristics, types, etc.). The following are examples of various combinations of image setting processes. For example, P0 to P5 of Fig. 11a may correspond to S0 to S5 of Fig. 11b, and a reconstruction process (rearrangement of pixels in this example) and a resizing process (same resizing to the division unit in this example) may be performed on the division unit. For example, resizing through an offset may be applied to P0 to P5 to be assigned to S0 to S5. In addition, P0 may be assigned to S0 without being reconstructed, P1 may be assigned to S1 by applying a 90-degree rotation, P2 may be assigned to S2 by applying a 180-degree rotation, P3 may be assigned to S3 by applying a 270-degree rotation, P4 may be assigned to S4 by applying a left-right inversion, and P5 may be assigned to S5 by applying an up-down inversion. For example, P0 to P5 in Fig. 11a may correspond to S0 to S5 in Fig. 11b at the same or different positions, and a reconstruction process (rearrangement of pixels and division units in this example) and a resizing process (same resizing of division units in this example) may be performed on the division units. For example, P0 to P5 may be assigned to S0 to S5 by applying resizing through a scale. In addition, P0 may be assigned to S0 without reconstructing, P1 may be assigned to S2 without reconstructing, P2 may be assigned to S1 by applying a 90-degree rotation, P3 may be assigned to S4 by applying a left-right inversion, P4 may be assigned to S5 by applying a 90-degree rotation and then a left-right inversion, and P5 may be assigned to S3 by applying a left-right inversion and then a 180-degree rotation. For example, P0 to P5 of Fig. 11a may correspond to E0 to E5 of Fig. 5e, and a reconstruction process (rearrangement of pixels and division units in this example) and a resizing process (unequal resizing of division units in this example) may be performed on the division units. For example, P0 may be assigned to E0 without performing resizing and reconstructing, P1 may be assigned to E1 without performing resizing through scale, P2 may be assigned to E2 without performing resizing through reconstruction, P3 may be assigned to E4 without performing resizing, P4 may be assigned to E5 without performing resizing through offset and reconstructing, and P5 may be assigned to E3 without performing resizing through offset and reconstructing. As in the above example, the absolute or relative position of the segmentation unit within the image before and after the image setting process may be maintained or changed, and this may be determined according to the encoding / decoding settings (e.g., the characteristics of the image, the type, etc.). In addition, a combination of various image setting processes may be possible, and variations to various examples may also be possible without being limited to the above example. In the above process, the information generated will be recorded in the bitstream as at least one unit such as a sequence, picture, slice, or tile by the encoder, and the related information will be parsed from the bitstream. In addition, it can be included in the bitstream in the form of SEI or metadata. The following shows examples of syntax elements related to multiple image settings. The examples described below will focus on additional syntax elements. In addition, the syntax elements in the examples described below are not limited to any specific unit and may be syntax elements supported by various units such as sequences, pictures, slices, and tiles. Or, they may be syntax elements included in SEI, metadata, etc. Referring to Table 4, parts_enabled_flag means a syntax element for whether or not to split some units. When enabled (parts_enabled_flag = 1), it means to split into multiple units and perform decoding / encoding, and additional segmentation information can be checked. When disabled (parts_enabled_flag = 0), it means to decode / encode the existing image. This example will be explained mainly based on rectangular segmentation units such as tiles, and can have different settings for existing tiles and segmentation information. num_partitions is a syntax element for the number of partition units, and a value added by 1 means the number of partition units. part_top[i] and part_left[i] are syntax elements for position information of a segmentation unit, and mean the horizontal and vertical start positions of the segmentation unit (for example, the upper left position of the segmentation unit). part_width[i] and part_height[i] are syntax elements for size information of the segmentation unit, and mean the horizontal and vertical lengths of the segmentation unit. At this time, the start position and size information can be set in pixel units or block units. In addition, the syntax elements may be syntax elements that can occur during an image reconstruction process, or may be syntax elements that can occur when an image segmentation process and an image reconstruction process are mixedly configured. part_header_enabled_flag is a syntax element for whether to support sub / decryption settings for the split unit. When enabled (part_header_enabled_flag = 1), the split unit can have sub / decryption settings, and when disabled (part_header_enabled_flag = 0), the split unit cannot have sub / decryption settings and can be assigned sub / decryption settings of the upper unit. The above example is not limited to an example of syntax elements related to resizing and reconstructing in the segmentation unit among the image settings described below, and changes to other segmentation units and settings of the present invention may be applied. This example is described under the assumption that resizing and reconstructing are performed after segmentation is performed, but is not limited thereto, and changes may be applied according to other image setting orders, etc. In addition, the types of syntax elements supported in the examples described below, the order of syntax elements, conditions, etc. are limited only to this example, and may be changed and determined according to the encoding / decoding settings. Table 5 shows examples of syntactic elements related to reconstruction at the segmentation unit level during image setup. Referring to Table 5, part_convert_flag[i] means a syntax element for whether to reconstruct a segmentation unit. The syntax element can occur for each segmentation unit, and when activated (part_convert_flag[i] = 1), it means to decode / uncode a reconstructed segmentation unit, and additional reconstruction-related information can be checked. When deactivated (part_convert_flag[i] = 0), it means to decode / uncode an existing segmentation unit. convert_type_flag[i] means mode information regarding the reconstructing of a segmentation unit, and may be information regarding the rearrangement of pixels. In addition, syntactic elements for additional reconstruction, such as reordering of segmentation units, may occur. In this example, reordering of segmentation units may be performed through the syntactic elements part_top and part_left for the image segmentation described above, or syntactic elements related to reordering of segmentation units (e.g., index information, etc.) may occur. Table 6 shows examples of syntax elements related to resizing at the segmentation unit level during image setup. Referring to Table 6, part_resizing_flag[i] means a syntax element for whether to resize the image of a segmentation unit. The syntax element can occur for each segmentation unit, and when activated (part_resizing_flag[i] = 1), it means to decode / encode the segmentation unit after resizing, and additional size-related information can be checked. When deactivated (part_resiznig_flag[i] = 0), it means to decode / encode the existing segmentation unit. width_scale[i] and height_scale[i] represent scale factors related to horizontal and vertical resizing in resizing through scale factors in the division unit. top_height_offset[i] and bottom_height_offset[i] represent the upper and lower offset factors related to the resizing via the offset factor in the division unit, and left_width_offset[i] and right_width_offset[i] represent the left and right offset factors related to the resizing via the offset factor in the division unit. resizing_type_flag[i][j] means a syntax element for a data processing method of an area to be resized in a partition unit. The syntax element means an individual data processing method for each direction of resizing. For example, a syntax element for an individual data processing method of an area to be resized in the up, down, left, and right directions may occur. This may also be generated based on resizing information (for example, it may occur only when resizing in some direction). The process of the aforementioned video settings may be applied depending on the characteristics, type, etc. of the video. In the examples described below, the aforementioned video settings process may be applied identically or may be applied in a modified manner even if there is no special mention. In the examples described below, the explanation will be centered on cases where additional or modified applications are applied to the aforementioned examples. For example, images generated through a 360-degree camera (360-degree video or omnidirectional video) have different characteristics from images acquired through a general camera, and have a different encoding environment from the compression of general images. Unlike general images, 360-degree images do not have boundaries with discontinuous characteristics, and data in all areas can have continuity. In addition, in devices such as HMD, images are played in front of the eyes through lenses, which may require high-quality images, and when images are acquired through stereoscopic cameras, the processed image data may increase. In order to provide an efficient encoding environment, including the above examples, various image setting processes considering 360-degree images can be performed. The above 360-degree camera may be a camera having multiple cameras or multiple lenses and sensors, and the camera or lenses may cover all directions around an arbitrary central point captured by the camera. 360-degree images can be encoded using various methods. For example, encoding can be performed using various image processing algorithms in a three-dimensional space, and encoding can also be performed using various image processing algorithms after converting to a two-dimensional space. In the present invention, a method of converting a 360-degree image to a two-dimensional space and performing encoding / decoding will be mainly described. A 360-degree video encoding device according to an embodiment of the present invention may be configured to include all or part of the configuration according to FIG. 1, and may further include a preprocessing unit that performs preprocessing (stitching, projection, region-wise packing) on ​​an input image. Meanwhile, a 360-degree video decoding device according to an embodiment of the present invention may include all or part of the configuration according to FIG. 2, and may further include a postprocessing unit that performs postprocessing (rendering) before the decoded image is reproduced as an output image. In other words, after the encoder performs a preprocessing process on the input image, encoding can be performed and a bitstream for the same can be transmitted, and the decoder can parse the transmitted bitstream, decode it, and generate an output image after a postprocessing process. At this time, the bitstream can contain and be transmitted information generated during the preprocessing process and information generated during the encoding process, and the decoder can parse it and use it during the decoding process and the postprocessing process. The following describes in more detail the operation method of the 360-degree video encoder. Since the operation method of the 360-degree video decoder is the opposite operation of the 360-degree video encoder, a person skilled in the art can easily derive it, and thus a detailed description is omitted. The input image can be stitched and projected onto a 3D projection structure in sphere units, and through the above process, image data on the 3D projection structure can be projected into a 2D image. The projected image can be configured to include all or part of the 360-degree content depending on the encoding settings. At this time, the location information of the area (or pixel) to be placed in the center of the projected image can be implicitly generated as a preset value or the location information can be explicitly generated. In addition, when the projected image is configured to include some area of ​​the 360-degree content, the range and location information of the included area can be generated. In addition, the range information (e.g., width and height) and location information (e.g., measurement based on the upper left corner of the image) for the region of interest (ROI) in the projected image can be generated. At this time, some area with high importance among the 360-degree content can be set as the region of interest. The 360-degree image can view all content in the up, down, left, and right directions, but the user's gaze can be limited to a part of the image, and this can be considered and set as the region of interest. For efficient encoding, the region of interest can be set to have good quality and resolution, and other regions can be set to have lower quality and resolution than the region of interest. Among the 360-degree video transmission methods, the single stream transmission method can transmit the entire video or the viewport video as a single individual bitstream for the user. The multi-stream transmission method transmits multiple entire videos with different video qualities as multiple bitstreams, so that the video quality can be selected according to the user environment and communication conditions. The tile stream transmission method transmits individually encoded partial videos of tile units as multiple bitstreams, so that the tiles can be selected according to the user environment and communication conditions. Therefore, a 360-degree video encoder generates and transmits bitstreams with two or more qualities, and a 360-degree video decoder can set a region of interest according to the user's gaze and selectively decode according to the region of interest. In other words, the place where the user's gaze stays can be set as the region of interest through a head tracking or eye tracking system, and rendering can be performed only on the necessary portion. The projected image can be converted into a packed image by performing a region-wise packing process. The region-wise packing process can include a step of dividing the projected image into multiple regions, and each of the divided regions can be arranged (or re-arranged) in the packed image according to the region-wise packing settings. The region-wise packing can be performed for the purpose of increasing spatial continuity when converting a 360-degree image into a 2D image (or a projected image), and can reduce the size of the image through the region-wise packing. In addition, it can be performed for the purpose of reducing image quality degradation that occurs during rendering, enabling viewport-based projection, and providing different types of projection formats. The region-wise packing can be performed or not performed depending on the encoding settings, and can be determined based on a signal indicating whether to perform it (for example, regionwise_packing_flag, in the example described below, information related to region-wise packing can occur only when regionwise_packing_flag is activated). When regional packaging is performed, setting information (or mapping information) that allocates (or places) a portion of a projected image to a portion of a packaged image can be displayed (or generated). When regional packaging is not performed, the projected image and the packaged image can be the same image. In the above, the stitching, projection, and regional packaging processes were defined as individual processes, but some of the processes (e.g., stitching + projection, projection + regional packaging) or all of the processes (e.g., stitching + projection + regional packaging) can be defined as a single process. At least one packaged image can be generated for the same input image according to the settings of the above stitching, projection, regional packaging process, etc. In addition, at least one encoded data for the same projected image can be generated according to the settings of the regional packaging process. The packaged image can be segmented by performing a tiling process. At this time, tiling is a process of dividing and transmitting an image into multiple regions, and can be an example of the 360-degree image transmission method. As described above, tiling can be performed for the purpose of partial decoding by considering the user environment, and can be performed for the purpose of efficient processing of a large amount of data of a 360-degree image. For example, if an image is composed of one unit, the entire image can be decoded for decoding a region of interest, but if the image is composed of multiple unit regions, it can be efficient to decode only the region of interest. At this time, the segmentation can be divided into tiles, which are segmentation units according to a conventional encoding method, or into various segmentation units (rectangular segmentations, blocks, etc.) described in the present invention. In addition, the segmentation unit can be a unit that performs independent sub / decoding. Tiling can be performed based on a projected image or a packaged image, or can be performed independently. That is, it can be divided based on the surface boundary of the projected image, the surface boundary of the packaged image, the packaging settings, etc., and each division unit can be divided independently. This can affect the generation of division information during the tiling process. Next, the projected image or the packaged image can be encoded. The encoded data and the information generated in the preprocessing process can be included in the bitstream and transmitted to the 360-degree image decoder. The information generated in the preprocessing process can also be included in the bitstream in the form of SEI or metadata. At this time, the bitstream can include at least one encoded data and at least one preprocessing information that change some settings of the encoding process or some settings of the preprocessing process. This may be for the purpose of configuring a decoded image by mixing a plurality of encoded data (encoded data + preprocessing information) according to the user environment in the decoder. Specifically, the decoded image can be configured by selectively combining a plurality of encoded data. In addition, the above process can be performed by separating it into two for application in a stereoscopic system, and the above process can be performed for an additional depth image. Figure 15 is an example diagram showing a three-dimensional space representing a three-dimensional image and a two-dimensional plane space. In general, 3DoF (Degree of Freedom) is required for a 360-degree three-dimensional virtual space, and can support three rotations around the X (Pitch), Y (Yaw), and Z (Roll) axes. DoF means a degree of freedom in space, and 3DoF means a degree of freedom that includes rotation around the X, Y, and Z axes as in 15a, and 6DoF means a degree of freedom that additionally allows movement along the X, Y, and Z axes in addition to 3DoF. The image encoding device and decoding device of the present invention will be described based on the case of 3DoF, and when supporting more than 3DoF (3DoF +), they may be combined with or modified with additional processes or devices not illustrated in the present invention. Referring to 15a, Yaw can range from -π(-180 degrees) to π(180 degrees), Pitch can range from -π / 2 rad (or -90 degrees) to π / 2 rad (or 90 degrees), and Roll can range from -π / 2 rad (or -90 degrees) to π / 2 rad (or 90 degrees). In this case, , θ are assumed to be longitude and latitude in the map representation of the Earth, and (x, y, z) in the three-dimensional space is ( , θ) can be converted from x = cos(θ). For example, x = cos(θ) cos( ), y = sin(θ), z = -cos(θ) sin( ) The coordinates of three-dimensional space can be derived from the coordinates of two-dimensional space according to the transformation formula. also, ( , θ) can be converted to (x, y, z). For example, = tan -1 (-Z / X), θ = sin - 1 (Y / (X 2 +Y 2 +Z 2 ) 1 / 2 ) can be used to derive two-dimensional space coordinates from three-dimensional space coordinates according to the conversion formula. When a pixel in a three-dimensional space is accurately converted into a two-dimensional space (for example, an integer unit pixel in a two-dimensional space), the pixel in the three-dimensional space can be mapped to a pixel in the two-dimensional space. When a pixel in the three-dimensional space is not accurately converted into a two-dimensional space (for example, a decimal unit pixel in a two-dimensional space), the two-dimensional pixel can be mapped to a pixel obtained by performing interpolation. At this time, the interpolation used may be a nearest neighbor interpolation method, a bi-linear interpolation method, a B-spline interpolation method, a bi-cubic interpolation method, etc. At this time, one of a plurality of interpolation candidates may be selected so that related information may be explicitly generated, or the interpolation method may be implicitly determined according to a preset rule. For example, a preset interpolation filter may be used according to a three-dimensional model, a projection format, a color format, a slice / tile type, etc. In addition, when interpolation information is explicitly generated, information about filter information (for example, filter coefficients, etc.) may also be included. 15b shows an example of transformation from three-dimensional space to two-dimensional space (two-dimensional plane coordinate system). ( ,θ) can be sampled (i,j) based on the size (width, height) of the image, where i can range from 0 to P_Width - 1, and j can range from 0 to P_Height - 1. ( ,θ) is the center point for arranging a 360-degree image as the center of the projected image {or reference point, the point indicated by C in Fig. 15, and the coordinates are ( ,θ)=(0,0)}. The setting for the center point can be specified in three-dimensional space, and the location information for the center point can be explicitly created or implicitly set to a preset value. For example, center location information in Yaw, center location information in Pitch, center location information in Roll, etc. can be created. If the value for the above information is not separately specified, each value can be assumed to be 0. The above example describes an example of converting the entire 360-degree image from a three-dimensional space to a two-dimensional space, but it can target a part of the 360-degree image, and location information (for example, some location belonging to the area, e.g., location information for the center point in this example), range information, etc. for the part of the image can be explicitly generated or implicitly follow preset location and range information. For example, center location information in Yaw, center location information in Pitch, center location information in Roll, range information in Yaw, range information in Pitch, range information in Roll, etc. can be generated, and in the case of a part of the image, there can be at least one area, and thus location information, range information, etc. of multiple areas can be processed. If a value for the above information is not separately specified, it can be assumed to be the entire 360-degree image. In 15a, H0 to H6 and W0 to W5 represent some latitude and longitude in 15b, respectively, and can be expressed as (C, j) and (i, C) in terms of coordinates of 15b (C is the longitude or latitude component). Unlike general images, in the case of 360-degree images, when converted to a two-dimensional space, distortion may occur or the contents in the image may be warped. This may occur differently depending on the area of ​​the image, and different encoding / decoding settings may be set for the location of the image or the area divided according to the location. In the case of adaptively setting the encoding / decoding settings based on the encoding / decoding information in the present invention, the location information (for example, x, y components or a range defined by x and y, etc.) may be included as an example of the encoding / decoding information. The above descriptions in three-dimensional and two-dimensional space are defined to help explain the embodiments of the present invention, and are not limited thereto, and modifications of details or application to other cases are possible. As described above, an image acquired by a 360-degree camera can be converted into a two-dimensional space. At this time, a 360-degree image can be mapped using a three-dimensional model, and various three-dimensional models such as a sphere, a cube, a cylinder, a pyramid, and a polyhedron can be used. When converting a 360-degree image mapped based on the above model into a two-dimensional space, a projection process according to a projection format based on the above model can be performed. FIGS. 16A to 16D are conceptual diagrams for explaining a projection format according to one embodiment of the present invention. Fig. 16a shows an ERP (Equi-Rectangular Projection) format that projects a 360-degree image onto a two-dimensional plane. Fig. 16b shows a CMP (CubeMap Projection) format that projects a 360-degree image onto a hexahedron. Fig. 16c shows an OHP (OctaHedron Projection) format that projects a 360-degree image onto an octahedron. Fig. 16d shows an ISP (IcoSahedral Projection) format that projects a 360-degree image onto a polyhedron. However, the present invention is not limited thereto, and various projection formats may be used. The left side of Figs. 16a to 16d shows a three-dimensional model, and the right side shows an example converted into a two-dimensional space through a projection process. Depending on the projection format, the projection format may have various sizes and shapes, and each shape may be composed of faces or surfaces, and the surfaces may be expressed as circles, triangles, squares, etc. In the present invention, the projection format can be defined by a 3D model, surface settings (e.g., number of surfaces, shape of surfaces, shape composition of surfaces, etc.), projection process settings, etc. If at least one element among the above definitions is different, it can be viewed as a different projection format. For example, in the case of ERP, it is composed of a sphere model (3D model), one surface (number of surfaces), and a square surface (shape of surfaces), but if some of the settings in the projection process (e.g., a formula used when converting from a 3D space to a 2D space, etc.; in other words, the remaining projection settings are the same, and the elements that make a difference in at least one pixel of the projection image in the projection process) are different, it can be classified into different formats, such as ERP1 and EPR2. As another example, in the case of CMP, it is composed of a cubic model, 6 surfaces, and a square surface, but if some of the settings in the projection process (e.g., a sampling method when converting from a 3D space to a 2D space) are different, it can be classified into different formats, such as CMP1 and CMP2. When using multiple projection formats rather than a single preset projection format, projection format identification information (or projection format information) can be explicitly generated. Projection format identification information can be configured in various ways. For example, multiple projection formats can be assigned index information (e.g., proj_format_flag) to identify the projection formats. For example, ERP can be assigned 0, CMP can be assigned 1, OHP can be assigned 2, ISP can be assigned 3, ERP1 can be assigned 4, CMP1 can be assigned 5, OHP1 can be assigned 6, ISP1 can be assigned 7, CMP compact can be assigned 8, OHP compact can be assigned 9, ISP compact can be assigned 10, and other formats can be assigned 11 or more. For example, a projection format can be identified by at least one element information that constitutes the projection format. At this time, the element information constituting the projection format may include 3D model information (e.g., 3d_model_flag. 0 is a sphere, 1 is a cube, 2 is a cylinder, 3 is a pyramid, 4 is polyhedron 1, 5 is polyhedron 2, etc.), surface number information (e.g., num_face_flag. starting from 1 and increasing by 1 or assigning the number of surfaces generated in the projection format as index information such that 0 is 1, 1 is 3, 2 is 6, 3 is 8, 4 is 20, etc.), surface shape information (e.g., shape_face_flag. 0 is a square, 1 is a circle, 2 is a triangle, 3 is square + circle, 4 is square + triangle, etc.), projection process setting information (e.g., 3d_2d_convert_idx, etc.). For example, the projection format can be identified by the projection format index information and the element information constituting the projection format. For example, the projection format index information can be assigned 0 for ERP, 1 for CMP, 2 for OHP, 3 for ISP, and 4 or more for other formats, and the projection format (for example, ERP, ERP1, CMP, CMP1, OHP, OHP1, ISP, ISP1, etc.) can be identified together with the element information constituting the projection format (in this example, projection process setting information). Alternatively, the projection format (for example, ERP, CMP, CMP compact, OHP, OHP compact, ISP, ISP compact, etc.) can be identified together with the element information constituting the projection format (whether or not it is packaged by region in this example). In summary, a projection format can be identified by projection format index information, can be identified by at least one projection format element information, and can be identified by projection format index information and at least one projection format element information. This can be defined according to encoding / decoding settings, and in the present invention, a description will be given assuming a case in which it is identified by a projection format index. In addition, although this example focuses on a case in which a projection format is expressed by surfaces having the same size and shape, a configuration in which the sizes and shapes of each surface are not the same may also be possible. In addition, the configuration of each surface may be the same as or different from those in FIGS. 16A to 16D, and the numbers of each surface are used as symbols for identifying each surface and are not limited to a specific order. For convenience of explanation, in the examples described below, ERP is a projection format with one surface + rectangle, CMP is a projection format with six surfaces + rectangles, OHP is a projection format with eight surfaces + triangles, and ISP is a projection format with 20 surfaces + triangles, and the surfaces have the same size and shape. However, the same or similar application may be possible to other settings. As shown in FIGS. 16A to 16D, the projection format can be divided into one surface (e.g., ERP) or multiple surfaces (e.g., CMP, OHP, ISP, etc.). In addition, each surface can be divided into shapes such as a square and a triangle. The above division can be an example of the type, characteristic, etc. of the image in the present invention that can be applied when different encoding / decoding settings are set according to the projection format. For example, the type of the image can be a 360-degree image, and the characteristic of the image can be one of the above divisions (e.g., each projection format, a projection format that is one surface or multiple surfaces, a projection format in which the surface is square or not, etc.). A two-dimensional planar coordinate system {e.g., (i,j)} can be defined for each surface of a two-dimensional projection image, and the characteristics of the coordinate system can vary depending on the projection format, the position of each surface, etc. In the case of ERP, there is one two-dimensional planar coordinate system, and other projection formats can have multiple two-dimensional planar coordinate systems depending on the number of surfaces. In this case, the coordinate system can be expressed as (k,i,j), where k can be the index information of each surface. Figure 17 is a conceptual diagram illustrating an implementation of a projection format according to one embodiment of the present invention as included within a rectangular image. That is, it can be understood that 17a to 17c are projection formats of FIGS. 16b to 16d implemented as rectangular images. Referring to 17a to 17c, each image format can be configured in a rectangular shape for encoding / decoding 360-degree images. In the case of ERP, it can be used as one coordinate system, but in the case of other projection formats, the coordinate systems of each surface can be integrated into one coordinate system, and a detailed description of this is omitted. Referring to FIGS. 17a to 17c, it can be confirmed that, in the process of configuring a rectangular image, an area filled with meaningless data, such as a blank space or background, occurs. That is, it can be composed of an area containing actual data (a surface in this example. Active Area) and a meaningless area filled to configure a rectangular image (assumed to be filled with an arbitrary pixel value in this example. Inactive Area). This can degrade performance due to an increase in the amount of encoded data due to an increase in the size of the image caused by the meaningless area as well as the encoding / decoding of actual image data. Therefore, an additional process can be performed to organize the image into areas that exclude meaningless areas and contain actual data. FIG. 18 is a conceptual diagram of a method for converting a projection format into a rectangular shape according to one embodiment of the present invention, wherein a surface is rearranged to exclude meaningless areas. Referring to 18a to 18c, an example of rearranging 17a to 17c can be confirmed, and this process can be defined as a regional packaging process (CMP compact, OHP compact, ISP compact, etc.). At this time, not only the surface itself can be rearranged, but the surface can also be divided and rearranged (OHP compact, ISP compact, etc.). This can be performed for the purpose of improving encoding performance through efficient arrangement of surfaces as well as removing meaningless areas. For example, if the arrangement has continuity in images between surfaces (for example, B2-B3-B1, B5-B0-B4 in 18a), the encoding performance can be improved by improving the prediction accuracy at the time of encoding. Here, regional packaging according to the projection format is only an example in the present invention and is not limited thereto. FIG. 19 is a conceptual diagram showing a regional packaging process performed on a rectangular image using a CMP projection format according to one embodiment of the present invention. Referring to 19a to 19c, the CMP projection format can be arranged as 6×1, 3×2, 2×3, 1×6. Also, when resizing is performed on some surfaces, the arrangement can be as in 19d to 19e. Although 19a to 19e exemplify CMP, it is not limited to CMP and may be applied to other projection formats. The surface arrangement of the image acquired through the above regional packaging can follow a preset rule according to the projection format or can explicitly generate information regarding the arrangement. A 360-degree video encoding / decoding device according to an embodiment of the present invention may be configured to include all or part of the video encoding / decoding devices according to FIGS. 1 and 2, and in particular, a format conversion unit and a format inverse conversion unit for converting and inversely converting a projection format may be further included in the video encoding device and the video decoding device, respectively. That is, in the video encoding device of FIG. 1, an input video may be encoded through a format conversion unit, and in the video decoding device of FIG. 2, an output video may be generated through a format inverse conversion unit after a bitstream is decoded. Hereinafter, the above process will be described with a focus on the encoder ('input video' to 'encoding' in this example), and the process in the decoder may be derived inversely from the encoder. In addition, any description overlapping with the above-mentioned content will be omitted. In the following, the input image is assumed to be the same image as the two-dimensional projection image or packaging image obtained by performing a preprocessing process in the aforementioned 360-degree encoding device. In other words, the input image may be an image obtained by performing a projection process according to some projection format or a regional packaging process. The projection format previously applied to the input image may be one of various projection formats, may be considered a common format, and may be referred to as the first format. The format conversion unit can perform conversion to a projection format other than the first format. At this time, the format to be converted can be referred to as the second format. For example, ERP can be set as the first format and conversion can be performed to the second format (e.g., ERP2, CMP, OHP, ISP, etc.). At this time, ERP2 can be an EPR format that has the same 3D model, surface configuration, etc. but has different settings. Alternatively, the projection format can be the same format (e.g., ERP = ERP2) and the size or resolution of the image can be different. Alternatively, some of the image setting processes described below can be applied. For convenience of explanation, the above example was given, but the first format and the second format can be one of various projection formats, and changes to other cases are also possible without being limited to the above example. In the process of converting between formats, since the pixels (integer pixels) of the image after conversion are sometimes obtained from not only the integer unit pixels of the image before conversion but also the decimal unit pixels due to the different coordinate system characteristics between the projection formats, interpolation can be performed. At this time, the interpolation filter used can use a filter that is the same as or similar to the above-mentioned filter. The interpolation filter can be explicitly generated by selecting one of a plurality of interpolation filter candidates, or can be implicitly determined according to a preset rule. For example, a preset interpolation filter can be used according to the projection format, color format, slice / tile type, etc. In addition, when the interpolation filter is explicitly sent, information about the filter (e.g., filter coefficients, etc.) can also be included. In the format conversion section, the projection format may be defined to include regional packaging, etc. That is, projection and regional packaging processes may be performed during the format conversion process. Alternatively, processes such as regional packaging may be performed after the format conversion section and before encoding. In the above process, the information generated will be recorded in the bitstream as at least one unit such as a sequence, picture, slice, or tile by the encoder, and the related information will be parsed from the bitstream. In addition, it can be included in the bitstream in the form of SEI or metadata. The following describes a video setting process applied to a 360-degree video encoding / decoding device according to an embodiment of the present invention. The video setting process in the present invention can be applied not only to a general encoding / decoding process, but also to a preprocessing process, a postprocessing process, a format conversion process, a format inverse conversion process, etc. in a 360-degree video encoding / decoding device. The video setting process described below will be described with a focus on a 360-degree video encoding device, and can be described including the contents of the video setting described above. Duplicate descriptions in the video setting process described above will be omitted. In addition, the examples described below will be described with a focus on the video setting process, and the video setting reverse process can be derived inversely from the video setting process, and in some cases, this can be confirmed through various embodiments of the present invention described above. The image setting process in the present invention can be performed at the projection stage of a 360-degree image, at the regional packaging stage, at the format conversion stage, or at other stages. Fig. 20 is a conceptual diagram for 360-degree image segmentation according to one embodiment of the present invention. Fig. 20 explains assuming the case of an image projected with ERP. 20a represents an image projected with ERP, and segmentation can be performed using various methods. In this example, the explanation is centered on slices and tiles, and it is assumed that W0 to W2 and H0 and H1 are segmentation boundaries of slices or tiles and follow the raster scan order. The example described below is centered on slices and tiles, but it is not limited thereto, and other segmentation methods can be applied. For example, the partitioning can be performed in slice units, and can have partition boundaries of H0, H1. Or, the partitioning can be performed in tile units, and can have partition boundaries of W0 to W2 and H0, H1. Fig. 20b shows an example of dividing an image projected by ERP into tiles {assuming that it has the same tile division boundaries (W0 to W2, H0, H1 are all activated) as Fig. 20a}. Assuming that region P is the entire image and region V is the region where the user's gaze stays or the viewport, there may be various methods to provide an image corresponding to the viewport. For example, the entire image (e.g., tiles a to l) can be decoded to obtain the region corresponding to the viewport. At this time, the entire image can be decoded, and if it is divided, tiles a to l (regions A + B in this example) can be decoded. Alternatively, the region corresponding to the viewport can be obtained by decoding the region belonging to the viewport. At this time, if it is divided, tiles f, g, j, k (region B in this example) can be decoded to obtain the region corresponding to the viewport in the restored image. The former can be called full decoding (or Viewport Independent Coding), and the latter can be called partial decoding (or Viewport Dependent Coding). The latter case can be an example that can occur in a 360-degree image with a large amount of data, and a tile-based segmentation method can be used more frequently than a slice-based segmentation method in that a segmentation area can be flexibly acquired. In the case of partial decoding, since it is not known where the viewport will occur, the referentiality of the segmentation unit can be limited spatially or temporally (implicitly processed in this example), and sub / decoding that takes this into consideration can be performed. The following example will explain with a focus on the case of full decoding, but in order to prepare for the case of partial decoding, a description will be given of 360-degree image segmentation centered on tiles (or the rectangular segmentation method of the present invention). However, the contents of the following example can be applied identically or with a change to other segmentation units. Fig. 21 is an example of 360-degree image segmentation and image reconstruction according to an embodiment of the present invention. Fig. 21 is explained assuming the case of an image projected with CMP. 21a represents an image projected by CMP, and segmentation can be performed using various methods. It is assumed that W0 to W2 and H0, H1 are segmentation boundaries of surfaces, slices, and tiles, and that they follow the raster scan order. For example, the division can be performed in slice units, and can have division boundaries of H0, H1. Or, the division can be performed in tile units, and can have division boundaries of W0 to W2 and H0, H1. Or, the division can be performed in surface units, and can have division boundaries of W0 to W2 and H0, H1. In this example, it is explained assuming that the surface is a part of the division unit. At this time, the surface may be a segmentation unit (dependent sub / decoding in this example) performed for the purpose of classifying or distinguishing areas having different properties (e.g., planar coordinate systems of each surface, etc.) within the same image according to the characteristics and type of the image (360-degree image, projection format in this example), and the slice and tile may be segmentation units (independent sub / decoding in this example) performed for the purpose of segmenting the image according to user definition. In addition, the surface may be a unit segmented by a preset definition (or derived from projection format information) in the projection process according to the projection format, and the slice and tile may be a unit segmented by explicitly generating segmentation information according to user definition. In addition, the surface may have a segmentation shape in a polygonal shape including a rectangle according to the projection format, the slice may have an arbitrary segmentation shape that cannot be defined as a rectangle or a polygon, and the tile may have a segmentation shape of a rectangle. The setting of the above segmentation unit may be a content defined in a limited manner for the explanation of this example. In the above example, the surface is described as a divided unit classified for the purpose of area division, but depending on the encoding / decoding setting, it can be a unit that performs independent encoding / decoding as at least one surface unit, or can have a setting that performs independent encoding / decoding in combination with tiles, slices, etc. In this case, in the combination with tiles, slices, etc., there may be a case where explicit information on tiles and slices is generated, or an implicit case where tiles and slices are combined based on surface information may occur. Alternatively, there may be a case where explicit information on tiles and slices is generated based on surface information. As a first example, a single image segmentation process (surface in this example) is performed, and the image segmentation can implicitly omit the segmentation information (obtain the segmentation information from the projection format information). This example may be an example for a dependent sub / decode setting, where the referentiality between surface units is not limited. As a second example, a single image segmentation process (surface in this example) is performed, and the image segmentation can explicitly generate segmentation information. This example may be an example for a dependent encoding / decoding setting, where the referentiality between surface units is not restricted. As a third example, multiple image segmentation processes (surfaces and tiles in this example) are performed, and some image segmentations (surfaces in this example) may implicitly omit or explicitly generate segmentation information, and some image segmentations (tiles in this example) may explicitly generate segmentation information. In this example, some image segmentation processes (surfaces in this example) precede some image segmentation processes (tiles in this example). As a fourth example, multiple image segmentation processes are performed, and some image segmentations (surfaces in this example) may implicitly omit segmentation information or explicitly generate segmentation information, and some image segmentations (tiles in this example) may explicitly generate segmentation information based on some image segmentations (surfaces in this example). In this example, some image segmentation processes (surfaces in this example) precede some image segmentation processes (tiles in this example). In this example, segmentation information is explicitly generated in some cases (assuming the case of the second example), but there may be differences in the configuration of segmentation information. As a fifth example, a plurality of image segmentation processes are performed, and some image segmentations (surfaces in this example) can implicitly omit segmentation information, and some image segmentations (tiles in this example) can implicitly omit segmentation information based on some image segmentations (surfaces in this example). For example, individual surface units can be set as tile units, or multiple surface units (in this example, if the neighboring surfaces are continuous surfaces, they are grouped, otherwise they are not grouped; B2-B3-B1 and B4-B0-B5 in 18a) can be set as tile units. Setting of surface units as tile units is possible according to preset rules. This example is an example of independent sub / decoding settings, and may be an example where the referential possibility between surface units is limited. That is, in some cases {assuming the case of the first example}, the segmentation information is implicitly processed, but there may be a difference in the sub / decoding settings. The above example may be an explanation of a case where the segmentation process may be performed at the projection stage, the regional packaging stage, the initial stage of sub-encoding / decoding, etc., and may be an image segmentation process that occurs within a sub-encoding / decoding unit. In 21a, a rectangular image can be configured including an area (B) that does not include data in an area (A) that includes data. At this time, the position, size, shape, number, etc. of areas A and B can be information that can be confirmed by a projection format, etc., or can be confirmed when information on the projected image is explicitly generated, and can be expressed as related information such as the image segmentation information, image reconstruction information, etc. described above. For example, as shown in Tables 4 and 5, information on some areas of the projected image (e.g., part_top, part_left, part_width, part_height, part_convert_flag, etc.) can be expressed, and is not limited to this example and can be an example applicable to other cases (e.g., other projection formats, other projection settings, etc.). The B region can be configured as a single image together with the A region to perform encoding / decoding. Alternatively, segmentation can be performed by considering the characteristics of each region, and different encoding / decoding settings can be set. For example, encoding / decoding can be not performed on the B region through information on whether encoding / decoding is performed (e.g., tile_coded_flag if the segmentation unit is a tile). At this time, the region can be restored to certain data (arbitrary pixel values ​​in this example) according to a preset rule. Alternatively, the encoding / decoding settings for the B region in the aforementioned image segmentation process can be different from those for the A region. Alternatively, the region can be removed by performing a packaging process for each region. 21b shows an example of dividing an image packaged with CMP into tiles, slices, and surfaces. At this time, the packaged image is an image in which a surface rearrangement process or a regional packaging process has been performed, and may be an image obtained by performing image segmentation or image reconstruction of the present invention. In 21b, a rectangular shape can be formed including an area including data. At this time, the location, size, shape, number, etc. of each area can be information that can be confirmed by preset settings or can be confirmed when information on a packaged image is explicitly generated, and related information can be indicated as the image segmentation information, image reconstruction information, etc. described above. For example, as shown in Table 4 and Table 5, information on some areas of a packaged image (e.g., part_top, part_left, part_width, part_height, part_convert_flag, etc.) can be indicated. The packaged image can be segmented using various segmentation methods. For example, segmentation can be performed on a slice-by-slice basis, and can have a segmentation boundary of H0. Or, segmentation can be performed on a tile-by-tile basis, and can have segmentation boundaries of W0, W1, and H0. Or, segmentation can be performed on a surface-by-surface basis, and can have segmentation boundaries of W0, W1, and H0. The image segmentation and image reconstruction process of the present invention can be performed on a projected image. At this time, the reconstruction process can rearrange not only pixels within a surface but also surfaces within the image. This can be a possible example when an image is divided or composed of multiple surfaces. The example described below will be explained mainly in the case where the image is divided into tiles based on surface units. SX,Y(S0,0 ~ S3,2) of 21a can correspond to S'U,V(S'0,0 ~ S'2,1. In this example, X, Y can be the same as or different from U, V) of 21b, and a reconstruction process can be performed on a surface unit. For example, S2,1, S3,1, S0,1, S1,2, S1,1, S1,0 can be assigned (or surface reassigned) to S'0,0, S'1,0, S'2,0, S'0,1, S'1,1, S'2,1. In addition, S2,1, S3,1, S0,1 can be reconstructed without performing reconstruction (or pixel reassignment), and S1,2, S1,1, S1,0 can be reconstructed by applying a 90 degree rotation, which can be expressed as in Fig. 21c. The symbols shown sideways in 21c (S1,0, S1,1, S1,2) may be images laid sideways to match the symbols to maintain continuity of the images. Surface reconstruction can be implicit or explicit depending on the encoding / decoding settings. In the implicit case, it can be performed according to preset rules considering the type of image (360-degree image in this example) and characteristics (projection format in this example). For example, in 21c, S'0,0 and S'1,0, S'1,0 and S'2,0, S'0,1 and S'1,1, S'1,1 and S'2,1 may be examples in which there is image continuity (or correlation) between the two surfaces based on the surface boundary, and 21c may be configured such that continuity exists between the upper three surfaces and the lower three surfaces. Through the projection process from a three-dimensional space to a two-dimensional space, the surfaces are divided into multiple surfaces and, in the process of going through regional packaging, the reconstruction may be performed for the purpose of increasing the image continuity between the surfaces for efficient reconstruction of the surfaces. The reconstruction of such surfaces may be preset and processed. Alternatively, the reconstruction process can be performed through explicit processing and reconstruction information can be generated for it. For example, if information (e.g., either implicitly acquired information or explicitly generated information) about an M×N configuration (e.g., 6×1, 3×2, 2×3, 1×6, etc. in the case of CMP compact, assuming a 3×2 configuration in this example) is identified through a regional packaging process, information about it can be generated after surface reconstruction is performed according to the M×N configuration. For example, in the case of intra-image rearrangement of a surface, index information (or intra-image position information) can be assigned to each surface, and in the case of intra-surface pixel rearrangement, mode information for the reconstruction can be assigned. Index information can be defined as in 18a to 18c of Fig. 18, and in 21a to 21c, SX, Y or S'U, V can be expressed as position information indicating the width and height of each surface (e.g., S[i][j]) or as a single position information (e.g., assuming that the position information is allocated in raster scan order from the upper left surface of the image, S[i]), and an index of each surface can be assigned to it. For example, when assigning indices with position information representing width and height, in the case of Fig. 21c, S'0,0 can be assigned to surface 2, S'1,0 to surface 3, S'2,0 to surface 1, S'0,1 to surface 5, S'1,1 to surface 0, and S'2,1 to surface 4. Alternatively, when assigning indices with one position information, S[0] can be assigned to surface 2, S[1] to surface 3, S[2] to surface 1, S[3] to surface 5, S[4] to surface 0, and S[5] to surface 4. For convenience of explanation, S'0,0 to S'2,1 are referred to as a to f in the examples described below. Alternatively, they can be expressed as position information representing width and height in pixel or block units based on the upper left corner of the image. For packaged images acquired through the reconstruction process (or regional packaging process) of the image, the scan order of the surface may or may not be the same in the image depending on the reconstruction settings. For example, when one scan order (e.g., raster scan) is applied to 21a, the scan orders of a, b, and c may be the same, and the scan orders of d, e, and f may not be the same. For example, when the scan order of 21a or a, b, and c follows the order of (0,0) -> (1,0) -> (0,1) -> (1,1), the scan order of d, e, and f may follow the order of (1,0) -> (1,1) -> (0,0) -> (0,1). This can be determined by the reconstruction settings of the image, and other projection formats may also have such settings. In the image segmentation process in 21b, individual surface units can be set as tiles. For example, surfaces a to f can each be set as tile units. Alternatively, multiple surface units can be set as tiles. For example, surfaces a to c can be set as one tile, and surfaces d to f can be set as one tile. The above configuration can be determined based on surface characteristics (e.g., continuity between surfaces, etc.), and tile settings of surfaces other than the above example can be possible. The following shows an example of segmentation information according to multiple image segmentation processes. In this example, segmentation information for the surface is omitted, units other than the surface are tiles, and the segmentation information is assumed to be processed in various ways. As a first example, image segmentation information can be implicitly omitted by obtaining it based on surface information. For example, individual surfaces can be set as tiles or multiple surfaces can be set as tiles. In this case, the case where at least one surface is set as a tile can be determined according to a preset rule based on surface information (e.g., continuity or correlation, etc.). As a second example, image segmentation information can be explicitly generated regardless of surface information. For example, when segmentation information is generated by the number of horizontal rows of tiles (num_tile_columns in this example) and the number of vertical rows (num_tile_rows in this example), the segmentation information can be generated by the method in the image segmentation process described above. For example, the ranges that the number of horizontal rows and the number of vertical rows of tiles can have can be from 0 to the width of the image / the width of the block (a unit obtained from the picture segmentation unit in this example), and from 0 to the height of the image / the height of the block. In addition, additional segmentation information (e.g., uniform_spacing_flag, etc.) can be generated. At this time, depending on the segmentation setting, the boundary of the surface and the boundary of the segmentation unit may or may not coincide. As a third example, image segmentation information can be explicitly generated based on surface information. For example, when segmentation information is generated by the number of horizontal rows and the number of vertical columns of tiles, segmentation information can be generated based on surface information (in this example, the range of the number of horizontal rows is 0 to 2, and the range of the number of vertical columns is 0 and 1, since the surface configuration in the image is 3x2). For example, the ranges that the number of horizontal rows and the number of vertical columns of tiles can have can be 0 to 2 and 0 to 1, respectively. In addition, additional segmentation information (e.g., uniform_spacing_flag, etc.) may not be generated. In this case, the boundary of the surface and the boundary of the segmentation unit may coincide. In some cases (assuming the second and third examples), the syntax elements of the segmentation information may be defined differently, or even if the same syntax elements are used, the syntax element settings (e.g., binarization settings, etc.; when the range of candidates for the syntax element is limited and small, a different binarization may be used, etc.) may be set differently. The above examples describe only a part of the various configurations of the segmentation information, but are not limited thereto, and may be understood as examples in which different settings are possible depending on whether the segmentation information is generated based on surface information. Figure 22 is an example of dividing an image projected by CMP or a packaged image into tiles. At this time, it is assumed that it has the same tile division boundary (W0 to W2, H0, H1 are all activated) as 21a of Fig. 21, and it is assumed that it has the same tile division boundary (W0, W1, H0 are all activated) as 21b of Fig. 21. When the P region is assumed to be the entire image and the V region is the viewport, full decoding or partial decoding can be performed. This example will explain mainly partial decoding. In 22a, in the case of CMP (left), tiles e, f, g can be decoded, and in the case of CMP compact (right), tiles a, c, e can be decoded to obtain an area corresponding to the viewport. In 22b, in the case of CMP, tiles b, f, i can be decoded, and in the case of CMP compact, tiles d, e, f can be decoded to obtain an area corresponding to the viewport. In the above example, the case where the segmentation such as slices, tiles, etc. is performed based on the surface unit (or surface boundary) is described, but it may also be possible to perform the segmentation within the surface (for example, ERP consists of one surface as an image. Other projection formats consist of multiple surfaces) as in 20a of Fig. 20, or to perform the segmentation including the surface boundary. Figure 23 is a conceptual diagram for explaining an example of resizing a 360-degree image according to one embodiment of the present invention. At this time, the explanation is given assuming the case of an image projected with ERP. In addition, the explanation is given focusing on the case of expansion in the examples described below. The projected image can be resized using a scale factor or an offset factor depending on the image resizing type. The image before resizing can be P_Width × P_Height, and the image after resizing can be P'_Width × P'_Height. For the scale factor, the width and height of the image can be resized using the scale factor (width a, height b in this example), and then the width (P_Width × a) and height (P_Height × b) of the image can be obtained. For the offset factor, the width and height of the image can be resized using the offset factor (width L, R, height T, B in this example), and then the width (P_Width + L + R) and height (P_Height + T + B) of the image can be obtained. Resizing can be performed using a preset method, or resizing can be performed by selecting one of multiple methods. The data processing method in the examples described below is explained mainly in the case of the offset factor. In the case of the offset factor, data processing methods may include a method of filling using preset pixel values, a method of filling by copying peripheral pixels, a method of filling by copying a portion of the image, and a method of filling by transforming a portion of the image. In the case of 360-degree images, resizing can be performed considering the characteristic that the boundaries of the images have continuity. In the case of ERP, there is no outer boundary in three-dimensional space, but when converted to two-dimensional space through the projection process, an outer boundary area may exist. This means that data in the boundary area has continuity outside the boundary, but may have boundaries due to the characteristics of the space. Resizing can be performed considering these characteristics. At this time, continuity can be confirmed according to the projection format, etc. For example, in the case of ERP, it can be an image that has the characteristic that the boundaries at both ends are continuous to each other. This example explains assuming the case where the left and right boundaries of the image are continuous and the case where the upper and lower boundaries are continuous, and the data processing method is explained focusing on the method of copying and filling a part of the image and the method of converting and filling a part of the image. When resizing to the left of the image, the area to be resized (LC or TL + LC + BL in this example) can be filled using data from the right area of ​​the image (tr + rc + br in this example) that has continuity with the left side of the image. When resizing to the right of the image, the area to be resized (RC or TR + RC + BR in this example) can be filled using data from the left area of ​​the image (tl + lc + bl in this example) that has continuity with the right side. When resizing to the top of the image, the area to be resized (TC or TL + TC + TR in this example) can be filled using data from the bottom area of ​​the image (bl + bc + br in this example) that has continuity with the top side. When resizing to the bottom of the image, the area to be resized (BC or BL + BC + BR in this example) can be filled using data. When the size or length of the region to be resized is m, the region to be resized can have a range of (-m, y) to (-1, y) (resized to the left) or a range of (P_Width, y) to (P_Width + m - 1, y) (resized to the right) with respect to the coordinates of the image before resizing (in this example, x is 0 to P_Width - 1). The position (x') of the region to acquire the data of the region to be resized can be derived by a formula according to x' = (x + P_Width) % P_Width. In this case, x means the coordinate of the region to be resized with respect to the image coordinates before resizing, and x' means the coordinate of the region referenced in the region to be resized with respect to the image coordinates before resizing. For example, when resizing to the left, if m is 4 and the image width is 16, (-4, y) can obtain the corresponding data from (12, y), (-3, y) from (13, y), (-2, y) from (14, y), and (-1, y) from (15, y). Or, when resizing to the right, if m is 4 and the image width is 16, (16, y) can obtain the corresponding data from (0, y), (17, y) from (1, y), (18, y) from (2, y), and (19, y) from (3, y). When the size or length of the region to be resized is n, the region to be resized can have a range of (x, -n) to (x, -1) (upper resizing) or a range of (x, P_Height) to (x, P_Height + n - 1) (lower resizing) with respect to the coordinates of the image before resizing (in this example, y is 0 to P_Height - 1). The position (y') of the region to obtain the data of the region to be resized can be derived by a formula such as y' = (y + P_Height) % P_Height. Here, y means the coordinate of the region to be resized with respect to the image coordinates before resizing, and y' means the coordinate of the region referenced in the region to be resized with respect to the image coordinates before resizing. For example, when performing upward resizing, if n is 4 and the vertical length of the image is 16, (x,-4) can obtain the corresponding data from (x,12), (x,-3) from (x,13), (x,-2) from (x,14), and (x,-1) from (x,15). Or, when performing downward resizing, if n is 4 and the vertical length of the image is 16, (x,16) can obtain the corresponding data from (x,0), (x,17) from (x,1), (x,18) from (x,2), and (x,19) from (x,3). After filling the data of the resized area, it can be adjusted to the image coordinates after resizing (in this example, x is 0 to P'_Width - 1, y is 0 to P'_Height - 1). The above example can be applied to the coordinate system of latitude and longitude. You can have a combination of different sizings, such as: For example, the image can be resized to the left by m. Or, the image can be resized to the right by n. Or, the image can be resized to the top by o. Or, the image can be resized to the bottom by p. For example, the image can be resized by m to the left and n to the right. Or, the image can be resized by o to the top and p to the bottom. For example, the image can be resized by m to the left, n to the right, and o upwards. Alternatively, the image can be resized by m to the left, n to the right, and p downwards. Alternatively, the image can be resized by m to the left, o upwards, and p downwards. Alternatively, the image can be resized by n to the right, o upwards, and p downwards. For example, the image can be resized by m to the left, n to the right, o to the top, and p to the bottom. At least one resizing can be performed as in the above example, and the resizing of the image can be performed implicitly according to the encoding / decoding settings, or the resizing information can be explicitly generated and the resizing of the image can be performed based on it. That is, m, n, o, and p in the above example can be set to preset values, or can be explicitly generated as resizing information, or some can be set to preset values ​​and some can be explicitly generated. The above example has been described mainly with reference to the case where data is acquired from a portion of an image, but other methods are also applicable. The data may be pixels before encoding or after encoding, and may be determined according to the characteristics of the image or step where resizing is performed. For example, when resizing is performed in a preprocessing step, a step before encoding, the data may refer to input pixels of a projection image, a packaged image, etc., and when resizing is performed in a postprocessing step, a step for generating intra-screen prediction reference pixels, a step for generating reference images, a filter step, etc., the data may refer to restored pixels. In addition, resizing may be performed individually for each resized area using a data processing method. FIG. 24 is a conceptual diagram for explaining continuity between surfaces in a projection format (e.g., CMP, OHP, ISP) according to one embodiment of the present invention. In detail, it can be an example of an image composed of a plurality of surfaces. Continuity can be a characteristic occurring in adjacent areas in a three-dimensional space, and FIGS. 24a to 24c can be classified into cases where they are spatially adjacent and have continuity (A), cases where they are spatially adjacent and have no continuity (B), cases where they are not spatially adjacent and have continuity (C), and cases where they are not spatially adjacent and have no continuity (D) when converted into a two-dimensional space through a projection process. There is a difference from general images being classified into cases where they are spatially adjacent and have continuity (A), cases where they are not spatially adjacent and have no continuity (D). In this case, cases where continuity exists correspond to some of the above examples (A or C). That is, referring to 24a to 24c, cases where they are spatially adjacent and have continuity (explained based on 24a in this example) can appear as b0 to b4, and cases where they are not spatially adjacent and have continuity can appear as B0 to B6. That is, this refers to cases of adjacent areas in three-dimensional space, and by utilizing the characteristic that b0 to b4 and B0 to B6 have continuity in the encoding process, the encoding performance can be improved. Figure 25 is a conceptual diagram for explaining the continuity of the surface of Figure 21c, which is an image obtained through an image reconstruction process or a regional packaging process in a CMP projection format. Here, since 21c of Fig. 21 is a rearrangement of 21a, which is a 360-degree image spread out in a cube shape, the continuity of the surface in 21a of Fig. 21 is maintained even at this time. That is, as in 25a, surface S2,1 is continuous with S1,1 and S3,1 left and right, and can be continuous with S1,0 rotated 90 degrees and S1,2 rotated -90 degrees up and down. In the same way, continuity for surface S3,1, surface S0,1, surface S1,2, surface S1,1, surface S1,0 can be verified in 25b to 25f. Continuity between surfaces can be defined according to projection format settings, etc., and is not limited to the above examples, and other examples of transformations may be possible. The examples described below are explained under the assumption that continuity such as those in Figs. 24 and 25 exists. FIG. 26 is an exemplary diagram for explaining image resizing in a CMP projection format according to one embodiment of the present invention. 26a shows an example of performing image resizing, 26b shows an example of performing resizing by surface unit (or by division unit), and 26c shows an example of performing resizing (or multiple resizing) by image and surface unit. The projected image can be resized using a scale factor or an offset factor depending on the image resizing type. The image before resizing is P_Width × P_Height, the image after resizing is P'_Width × P'_Height, and the size of the surface can be F_Width × F_Height. The sizes can be the same or different depending on the surface, and the width and height of the surfaces can be the same or different. However, in this example, for the convenience of explanation, it is assumed that the sizes of all surfaces in the image are the same and have a square shape. In addition, it is assumed that the resizing values ​​(WX and HY in this example) are the same. The data processing method in the examples described below will be explained focusing on the case of the offset factor, and the data processing method will be explained focusing on the method of copying and filling a portion of the image and the method of transforming and filling a portion of the image. The above settings can be equally applied to FIG. 27. In the case of 26a to 26c, the boundary of the surface (assuming continuity according to 24a of Fig. 24 in this example) can have continuity with the boundary of another surface. At this time, it can be distinguished into a case where they are spatially adjacent in a two-dimensional plane and there is continuity of the image (first example) and a case where they are not spatially adjacent in a two-dimensional plane and there is continuity of the image (second example). For example, assuming the continuity of 24a in Fig. 24, the upper, left, right, and lower regions of S1,1 may be spatially adjacent to the lower, right, left, and upper regions of S1,0, S0,1, S2,1, and S1,2, and the images may also be continuous (in the case of the first example). Alternatively, the left and right regions of S1,0 may not be spatially adjacent to the upper regions of S0,1 and S2,1, but their images may be continuous (in the second example). In addition, the left region of S0,1 and the right region of S3,1 may not be spatially adjacent to each other, but their images may be continuous (in the second example). In addition, the left region and the right region of S1,2 may be continuous (in the second example) with the lower regions of S0,1 and S2,1. This may be a limited example in this example, and may have a different configuration than the above depending on the definition and setting of the projection format. For convenience of explanation, S0,0 to S3,2 in Fig. 26a are referred to as a to l. 26a can be an example of filling using data of an area where continuity exists in the direction of the outer boundary of the image. An area resized from an area A where no data exists (a0 to a2, c0, d0 to d2, i0 to i2, k0, l0 to l2 in this example) can be filled using a preset arbitrary value or outer pixel padding, and an area resized from an area B that includes actual data (b0, e0, h0, j0 in this example) can be filled using data of an area (or surface) where continuity exists in the image. For example, b0 can be filled using data of the upper side of surface h, e0 can be filled using data of the right side of surface h, h0 can be filled using data of the left side of surface e, and j0 can be filled using data of the lower side of surface h. Specifically, b0 may be an example in which the data on the lower side of the surface obtained by applying a 180-degree rotation to surface h is filled, and j0 may be an example in which the data on the upper side of the surface obtained by applying a 180-degree rotation to surface h is filled, but in this example (or the example described below), only the position of the referenced surface will be indicated, and the data acquired in the area to be resized may be acquired after going through an adjustment process (e.g., rotation, etc.) that takes into account the continuity between the surfaces, as in FIGS. 24 and 25. 26b can be an example of filling using data of an area where continuity exists in the direction of the inner boundary of the image. In this example, the resizing operation performed depending on the surface can be different. Area A can perform a reduction process and area B can perform an expansion process. For example, for surface a, resizing by w0 to the right (reduction in this example) can be performed, and for surface b, resizing by w0 to the left (expansion in this example) can be performed. Alternatively, for surface a, resizing by h0 to the bottom (reduction in this example) can be performed, and for surface e, resizing by h0 to the top (expansion in this example) can be performed. In this example, when looking at the change in the horizontal length of the image to surfaces a, b, c, and d, surface a is reduced by w0, surface b is expanded by w0 and w1, and surface c is reduced by w1, so the horizontal length of the image before resizing and the horizontal length of the image after resizing are the same. When looking at the change in the vertical length of the image with surfaces a, e, and i, the vertical length of the image before resizing and the vertical length of the image after resizing are the same because surface a is reduced by h0, surface e is expanded by h0 and h1, and surface i is reduced by h1. The resized region (b0, e0, be, b1, bg, g0, h0, e1, ej, j0, gi, g1, j1, h1 in this example) can be simply removed, considering that it is shrinking from a region A where no data exists, or it can be newly filled with data from a region where there is continuity, considering that it is expanding from a region B that contains actual data. For example, b0 can be filled using data from the top of surface e, e0 can be filled using data from the left of surface b, be can be filled using data from the left of surface b or the top of surface e, or the weighted sum of the left of surface b and the top of surface e, b1 can be filled using data from the top of surface g, bg can be filled using data from the left of surface b or the top of surface g, or the weighted sum of the right of surface b and the top of surface g, g0 can be filled using data from the right of surface b, h0 can be filled using data from the top of surface b, e1 can be filled using data from the left of surface j, ej can be filled using data from the lower of surface e or the left of surface j, or the weighted sum of the lower of surface e and the left of surface j, j0 can be filled using data from the lower of surface e, gj can be filled using data from the lower of surface g or the left of surface j, or the weighted sum of the lower of surface g and the right of surface j, g1 can be filled using data from the right of surface j, j1 can be filled using data from the lower of surface g, and h1 can be filled using data from the lower of surface j. In the above example, when filling in the area to be resized using data from a part of the image, the data from that area can be copied and filled in, or the data from that area can be filled in after undergoing a conversion process based on the characteristics, type, etc. of the image. For example, when a 360-degree image is converted into a two-dimensional space according to a projection format, a coordinate system (e.g., a two-dimensional plane coordinate system) of each surface can be defined. For convenience of explanation, let us assume that (x, y, z) in the three-dimensional space has been converted to (x, y, C) or (x, C, z) or (C, y, z) for each surface. The above example shows a case where data from a surface other than that surface is acquired in the area to be resized. In other words, when resizing is performed centered on the current surface, if data from another surface with different coordinate system characteristics is copied and filled in as is, there is a possibility that continuity may be distorted based on the resizing boundary. To this end, data from another surface acquired according to the coordinate system characteristics of the current surface can be converted and filled in the area to be resized. In the case of conversion, this is only an example of a method of data processing and is not limited thereto. When copying and filling data from a portion of an image into a resized area, the boundary area between the resized area (e) and the resized area (e0) may contain distorted continuity (or radically changing continuity). For example, a continuous feature may change based on the boundary, such as an edge that was a straight line becoming a bent shape based on the boundary. When filling a portion of an image by transforming data into the area being resized, it may include continuity that gradually changes between the area being resized and the boundary area of ​​the area being resized. The above example may be an example of a data processing method of the present invention, which performs a conversion process on data of a part of an image in a resizing process (expansion in this example) based on the characteristics, type, etc. of the image, and fills the acquired data into the resized area. 26c can be an example of combining the image resizing process according to 26a and 26b to fill in data in an area where continuity exists in the direction of the image boundary (inner boundary and outer boundary). Since the resizing process of this example can be derived from 26a and 26b, a detailed description is omitted. 26a may be an example of a resizing process of an image, 26b may be an example of a resizing process of a segmentation unit within an image, and 26c may be an example of a plurality of resizing processes in which a resizing process of an image and a resizing process of a segmentation unit within an image are performed. For example, resizing (area C in this example) can be performed on an image (format 1 in this example) acquired through a projection process, and resizing (area D in this example) can be performed on an image (format 2 in this example) acquired through a format conversion process. In this example, resizing (the entire image in this example) can be performed on an image projected as ERP, and then resizing (surface unit in this example) can be performed after acquiring an image projected as CMP through a format conversion unit. The above example is an example of performing multiple resizing, and is not limited thereto, and variations to other cases may also be possible. Fig. 27 is an exemplary diagram for explaining resizing of a packaged image converted into a CMP projection format according to one embodiment of the present invention. Since Fig. 27 also explains on the premise of surface continuity according to Fig. 25, the boundary of a surface can have continuity with the boundary of another surface. In this example, the offset factors of W0 to W5 and H0 to H3 (assuming that the offset factors are used as the resizing values ​​in this example) can have various values. For example, they can be derived from preset values, motion search ranges of inter-screen prediction, units obtained from the picture segmentation unit, etc., and other cases are also possible. In this case, the units obtained from the picture segmentation unit can include a surface. That is, the resizing values ​​can be determined based on F_Width and F_Height. 27a is an example of filling in data in an area where continuity exists in each area that is expanded by performing scaling (in this example, in the up, down, left, and right directions of each surface) for each surface. For example, for surface a, continuous data can be filled in the outer perimeter a0 to a6, and continuous data can be filled in the outer perimeter b0 to b6 of surface b. 27b is an example of filling in data in an area where continuity exists in the expanded area by performing scaling (up, down, left, right directions of multiple surfaces in this example) for multiple surfaces. For example, based on surfaces a, b, and c, the perimeter can be expanded to a0~a4, b0~b1, and c0~c4. 27c can be an example of filling in data in an area where continuity exists in the expanded area by performing resizing of the entire image (in this example, in the up, down, left, and right directions of the entire image). For example, the perimeter of the entire image consisting of surfaces a to f can be expanded to a0 to a2, b0, c0~c2, d0~d2, e0, f0~f2. That is, resizing can be performed on a single surface unit, resizing can be performed on multiple surface units where continuity exists, and resizing can be performed on the entire surface unit. The resized area of ​​the above example (a0 to f7 in this example) can be filled using data of an area (or surface) where continuity exists, as in Fig. 24a. That is, the resized area can be filled using data of the upper, lower, left, and right sides of surfaces a to f. FIG. 28 is an exemplary diagram for explaining a data processing method in resizing a 360-degree image according to one embodiment of the present invention. Referring to FIG. 28, the area B (a0 to a2, ad0, b0, c0 to c2, cf1, d0 to d2, e0, f0 to f2) to be resized can be filled with data from an area where continuity exists among pixel data belonging to a to f. In addition, the area C (ad1, be, cf0), which is another area to be resized, can be filled by mixing data from an area where resizing is performed and data from an area where resizing is performed but where continuity does not exist. Alternatively, the area C can be filled by mixing data from two areas selected from a to f (e.g., a and d, b and e, c and f). For example, surface b and surface e may have a relationship where they are spatially adjacent but where continuity does not exist. Resizing can be performed using data from surface b and data from surface e in the area (be) to be resized between surface b and surface e. For example, the be area can be filled with a value obtained by averaging the data of surface b and the data of surface e, or with a value obtained through a weighted sum according to the distance. At this time, the pixels used for the data to be filled in the area to be resized on surface b and surface e can be the boundary pixels of each surface, but can also be the interior pixels of the surfaces. In summary, the area to be resized between the image segmentation units can be filled with data generated by mixing data from both units. The above data processing method may be supported in some situations (in this example, when performing resizing in multiple areas). In Figs. 27a and 27b, regions where resizing is performed between the division units are individually configured for each division unit (for example, in Fig. 27a, a6 and d1 are configured for a and d, respectively), but in Fig. 28, regions where resizing is performed between the division units can be configured one by one for adjacent division units (one ad1 for a and d). Of course, Figs. 27a to 27c can also include the above method as a candidate for the data processing method, and in Fig. 28, resizing can be performed using a data processing method different from the above example. In the process of resizing an image of the present invention, a data processing method implicitly set in the resized area can be used, or one of a plurality of data processing methods can be used and related information can be explicitly generated. The preset data processing method can be one of the following data processing methods: a method of filling using an arbitrary pixel value, a method of filling by copying peripheral pixels, a method of filling by copying a portion of an image, a method of filling by transforming a portion of an image, a method of filling by data derived from a plurality of areas of an image, etc. For example, when the area to be resized is located inside an image (e.g., a wrapped image) and the areas on both sides (e.g., surfaces) are spatially adjacent but do not have continuity, a data processing method of filling by data derived from a plurality of areas can be applied to fill the area to be resized. In addition, resizing can be performed by selecting one of the plurality of data processing methods, and selection information for this can be explicitly generated. This can be an example that can be applied not only to 360-degree images but also to general images. In the above process, the information generated will be recorded in the bitstream as at least one unit such as a sequence, picture, slice, or tile in the encoder, and the related information will be parsed from the bitstream. In addition, it can be included in the bitstream in the form of SEI or metadata. The process of segmentation, reconstruction, and resizing in 360-degree images has been described with a focus on some projection formats such as ERP and CMP, but it is not limited thereto and can be applied to other projection formats in the same manner or with changes. It was explained that the video setting process applied to the aforementioned 360-degree video encoding / decoding device can be applied not only to the encoding / decoding process but also to the preprocessing process, postprocessing process, format conversion process, and format inverse conversion process. In summary, the projection process can be configured to include an image setting process. Specifically, the projection process can be performed by including at least one image setting process. Segmentation can be performed in units of regions (or surfaces) based on the projected image. Segmentation can be performed in one region or multiple regions depending on the projection format. Segmentation information according to the segmentation can be generated. In addition, resizing of the projected image can be performed or resizing of the projected region can be performed. At this time, resizing can be performed in at least one region. Resizing information according to the resizing can be generated. In addition, reconstruction (or surface layout) of the projected image can be performed or reconstructing of the projected region can be performed. At this time, reconstruction can be performed in at least one region. Reconstruction information according to the reconstructing can be generated. In summary, the regional packaging process can be configured to include an image setting process. Specifically, the regional packaging process can be performed by including at least one image setting process. The segmentation process can be performed in units of regions (or surfaces) based on the packaged image. The segmentation can be performed into one region or multiple regions according to the regional packaging setting. Segmentation information according to the segmentation can be generated. In addition, the size of the packaged image can be adjusted or the size of the packaged region can be adjusted. At this time, the size adjustment can be performed into at least one region. The size adjustment information according to the size adjustment can be generated. In addition, the reconstruction of the packaged image can be performed or the reconstruction of the packaged region can be performed. At this time, the reconstruction can be performed into at least one region. The reconstruction information according to the reconstruction can be generated. The above projection process may perform all or part of the image setting process and may include image setting information. This may be setting information of the projected image. Specifically, it may be setting information of areas within the projected image. The above regional packaging process may perform all or part of the image setting process and may include image setting information. This may be setting information of the packaged image. Specifically, it may be setting information of areas within the packaged image. Or, it may be mapping information of the projected image and the packaged image (for example, see the description related to FIG. 11. It may be understood that P0 to P1 are projected images and S0 to S5 are packaged images). Specifically, it may be mapping information of a part of the projected image and a part of the packaged image. That is, it may be setting information that is allocated from a part of the projected image to a part of the packaged image. The above information can be represented as information obtained through various embodiments described above in the image setting process of the present invention. For example, when representing related information using at least one syntax element from Tables 1 to 6, the configuration information of the projected image may include pic_width_in_samples, pic_height_in_samples, part_top[i], part_left[i], part_width[i], part_height[i], etc., and the configuration information of the packed image may include pic_width_in_samples, pic_height_in_samples, part_top[i], part_left[i], part_width[i], part_height[i], convert_type_flag[i], part_resizing_flag[i], top_height_offset[i], bottom_height_offset[i], left_width_offset[i], right_width_offset[i], resizing_type_flag[i], etc. The above example may be an example of explicitly generating information about the surface (e.g., part_top[i], part_left[i], part_width[i], part_height[i] among the setup information of the projected image). Part of the image setup process can be included in the projection process according to the projection format or the packaging process according to the region as a preset action. For example, in the case of ERP, a process of performing resizing may be implicitly included by filling an area that is expanded by m, n in the left and right directions, respectively, by copying data from an area in the opposite direction of the image resizing direction (right and left in this example). Alternatively, in the case of CMP, a process of performing resizing may be implicitly included by filling an area that is expanded by m, n, o, and p in the up, down, left, and right directions, respectively, by transforming data from an area that is continuous with the area where resizing is performed. The projection format of the above example may be an example of replacing an existing projection format, or may be an example of an additional projection format (e.g., ERP1, CMP1) to an existing projection format, and is not limited to the above example, and examples of various image setting processes of the present invention may be replaced and combined, and similar applications may also be possible for other formats. Meanwhile, although not illustrated in the image encoding device and image decoding device of FIGS. 1 and 2, a block division unit may be further included. Information on a basic encoding unit may be obtained from the picture division unit, and the basic encoding unit may mean a basic (or start) unit for prediction, transformation, quantization, etc. in the image encoding / decoding process. At this time, the encoding unit may be composed of one luminance encoding block and two chrominance encoding blocks according to the color format (YCbCr in this example), and the size of each block may be determined according to the color format. The following examples will explain based on blocks (luminance components in this example). At this time, it is assumed that a block is a unit that can be obtained after each unit is determined, and it is explained assuming that similar settings can be applied to other types of blocks. The block division unit can be set in relation to each component of the video encoding device and the decoding device, and the size and shape of the block can be determined through this process. At this time, the set block can be defined differently depending on the component, and can correspond to a prediction block in the case of the prediction unit, a transformation block in the case of the transformation unit, and a quantization block in the case of the quantization unit. The present invention is not limited thereto, and block units according to other components can be additionally defined. The size and shape of the block can be defined by the horizontal and vertical lengths of the block. In the block partition, a block can be expressed as M × N, and the maximum and minimum values ​​of each block can be obtained within a range. For example, if the shape of the block supports a square and the maximum value of the block is set to 256 × 256 and the minimum value is set to 8 × 8, 2 m ×2 m A block of size (in this example, m is an integer from 3 to 8. For example, 8×8, 16×16, 32×32, 64×64, 128×128, 256×256) or a block of size 2m×2m (in this example, m is an integer from 4 to 128) or a block of size m×m (in this example, m is an integer from 8 to 256). Or, if the shape of the block supports square and rectangle and has the same range as the above example, 2 m × 2 n You can obtain a block of the size of (in this example, m and n are integers from 3 to 8. Assuming a width-to-height ratio of at most 2:1, for example, 8×8, 8×16, 16×8, 16×16, 16×32, 32×16, 32×32, 32×64, 64×32, 64×64, 64×128, 128×64, 128×128, 128×256, 256×128, 256×256. There may be no restriction on the width-to-height ratio or a maximum value for the ratio depending on the encoding / decoding settings.) Or, you can obtain a block of the size of 2m × 2n (in this example, m and n are integers from 4 to 128). Alternatively, we can obtain blocks of size m × n (where m and n are integers from 8 to 256 in this example). The obtainable blocks can be determined depending on the encoding / decoding settings (e.g., block type, partitioning method, partitioning settings, etc.). For example, the encoding block is 2 m × 2 n Blocks of size 2m × 2n or m × n, prediction blocks are blocks of size 2m × 2n or m × n, transformation blocks are blocks of size 2 m × 2 n A block of size can be obtained. Based on the above settings, information such as block size, range, etc. (e.g., information related to exponents, multiples, etc.) can be generated. The above range (defined as maximum and minimum values ​​in this example) may be determined depending on the type of block. In addition, some blocks may have their range information explicitly generated, and some blocks may have their range information implicitly determined. For example, encoding and transformation blocks may have their related informati...

Claims

1. In the decoding method of 360-degree video, A step of receiving a bitstream in which a 360-degree video is encoded; A step of generating a predicted image by referring to syntax information obtained from a received bitstream; A step of obtaining a decoded image by combining the generated predicted image with a residual image obtained by inversely quantizing and inversely transforming the bitstream; and It includes a step of reconstructing the above decrypted image into a 360-degree image according to the projection format, The step of generating the above predicted image is: A step of obtaining a motion vector candidate group including the motion vectors of the current block to be decoded and the adjacent blocks from the motion information included in the above syntax information; A step of deriving a predicted motion vector from among a group of motion vector candidates based on selection information extracted from the above motion information; and A method for decoding a 360-degree video, comprising a step of determining a prediction block of a current block to be decoded by using a final motion vector derived by adding the predicted motion vector to a differential motion vector extracted from the motion information.

2. In claim 1, The above motion vector candidates are: If the block adjacent to the current block is different from the surface to which the current block belongs, A method for decoding a 360-degree image, the method comprising motion vectors only for blocks belonging to a surface having image continuity with the surface to which the current block belongs, among the adjacent blocks.

3. In claim 1, The above adjacent blocks are, A method for decoding a 360-degree image, wherein the method means a block adjacent to the current block in at least one of the upper left, upper right, left, and lower left directions.

Images