Image compression method and device, electronic equipment and storage medium

Abstract

The invention relates to the field of computer image compression, in particular to an image compression method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining a current compression demand, a current compression rule, a current variable rendering rate parameter and a to-be-compressed image, and determining a target compression rate curve according to the current compression demand and the current compression rule, and generating a first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter, and performing mapping compression on the to-be-compressed image based on the first pixel coordinate mapping function to obtain a compressed image. Therefore, the image is compressed by using the pixel coordinate mapping function, the problems that a large number of computing resources need to be consumed, the storage space requirement is large and the display effect of the compressed image is poor when the image is compressed at the present stage are solved, and the visual experience of a user is improved.

Description

Technical Field

[0001] The present application relates to the field of computer image compression, and in particular to an image compression method, device, electronic device and storage medium. Background Art

[0002] Image compression refers to an image processing method that reduces the number of bits required to represent image data by removing redundant data, which can save storage resources and improve data transmission efficiency.

[0003] In the related art, most mainstream compression algorithms use regional block compression algorithms.

[0004] However, this method compresses and decompresses each block independently, which consumes a lot of computing resources. The compressed image needs to be saved in blocks, which requires a large amount of storage space. In addition, the display effect of the compressed image is poor, which needs to be solved urgently. Summary of the invention

[0005] The present application provides an image compression method, device, electronic device and storage medium to solve the current problem of consuming a large amount of computing resources and requiring a large storage space when compressing images, as well as the problem of poor display effect of compressed images, thereby improving the user's visual experience.

[0006] To achieve the above object, the first embodiment of the present application provides an image compression method, comprising the following steps:

[0007] Get the current compression requirement, current compression rule, current variable rendering rate parameter and the image to be compressed;

[0008] Determining a target compression rate curve according to the current compression requirement and the current compression rule, and generating a first pixel coordinate mapping function according to the target compression rate curve and a current variable rendering rate parameter; and

[0009] Based on the first pixel coordinate mapping function, the image to be compressed is mapped and compressed to obtain a compressed image.

[0010] According to an embodiment of the present application, the current compression rule is to determine an uncompressed area, and / or a gradually compressed area, and / or a maximum compressed area of ​​the image to be compressed;

[0011] The uncompressed area is an area of ​​a first preset size corresponding to the coordinates of the current compression center point or the gaze point coordinates;

[0012] The gradually compressed area is an area of ​​a second preset size adjacent to the non-compressed area;

[0013] The maximum compression area is the area of the image to be compressed excluding the non-compression area and the gradient compression area.

[0014] According to an embodiment of the present application, the current compression requirement is the requirement that the resolution of the compressed image remains unchanged, or the requirement that the resolution of the compressed image is determined by the updated fixation point coordinates.

[0015] According to an embodiment of the present application, if the current compression requirement is that the resolution of the compressed image remains unchanged, while obtaining the target compression rate curve, obtain the current compression center point coordinates;

[0016] The generating the first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter includes:

[0017] Generate the first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve and the current compression center point coordinates.

[0018] According to an embodiment of the present application, if the current compression requirement is that the resolution of the compressed image is determined by the updated fixation point coordinates, while obtaining the target compression rate curve, obtain the user's fixation point coordinates;

[0019] The generating the first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter includes:

[0020] Generate the first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve and the fixation point coordinates.

[0021] According to an embodiment of the present application, the mapping compression of the image to be compressed based on the first pixel coordinate mapping function to obtain a compressed image includes:

[0022] Use the first pixel coordinate mapping function to perform mapping compression on the horizontal and vertical pixel coordinates of the image to be compressed to obtain compressed horizontal and vertical pixel coordinates;

[0023] Based on the correspondence between the horizontal and vertical pixel coordinates of the image to be compressed and the compressed horizontal and vertical pixel coordinates, determine the color value of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates according to the color value of the pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed;

[0024] Converge the color values of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates to obtain the compressed image.

[0025] According to an embodiment of the present application, the pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed.

[0026] According to an embodiment of the present application, some of the pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed, and the remaining pixel points have no corresponding relationship with the pixel points of the image to be compressed or the remaining pixel points have a corresponding relationship with multiple pixel points of the image to be compressed.

[0027] According to an embodiment of the present application, each point on the first pixel coordinate mapping function corresponds to a compression ratio value.

[0028] According to an embodiment of the present application, there are points on the first pixel coordinate mapping function that correspond to multiple compression ratio values.

[0029] According to an embodiment of the present application, after obtaining the compressed image, it further includes:

[0030] Based on the second pixel coordinate mapping function, the compressed image is subjected to mapping decompression to obtain the image to be compressed.

[0031] According to the image compression method proposed by the embodiment of the present application, by obtaining the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed, the target compression ratio curve can be determined according to the current compression requirement and the current compression rule, and the first pixel coordinate mapping function can be generated according to the target compression ratio curve and the current variable rendering rate parameter. Based on the first pixel coordinate mapping function, the image to be compressed is subjected to mapping compression to obtain the compressed image. Thus, by using the pixel coordinate mapping function to compress the image, the problems that a large amount of computing resources need to be consumed and the storage space requirement is large when compressing the image at the present stage, as well as the problem that the display effect of the compressed image is poor, are solved, and the visual experience of the user is improved.

[0032] To achieve the above object, an embodiment of the second aspect of the present application proposes an image compression device, including:

[0033] An acquisition module, configured to acquire the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed;

[0034] A generation module, configured to determine a target compression ratio curve according to the current compression requirement and the current compression rule, and generate a first pixel coordinate mapping function according to the target compression ratio curve and the current variable rendering rate parameter; and

[0035] A compression module, configured to perform mapping compression on the image to be compressed based on the first pixel coordinate mapping function to obtain the compressed image.

[0036] According to an embodiment of the present application, the current compression rule is to determine the uncompressed area, and / or, the gradually compressed area, and / or, the maximum compressed area of the image to be compressed;

[0037] Wherein, the uncompressed area is an area with a first preset size corresponding to the current compression center point coordinates or the gaze point coordinates;

[0038] The gradually compressed area is an area with a second preset size adjacent to the uncompressed area;

[0039] The maximum compressed area is the area of the image to be compressed other than the uncompressed area and the gradually compressed area.

[0040] According to an embodiment of the present application, the current compression requirement is the requirement that the resolution of the compressed image remains unchanged, or the requirement that the resolution of the compressed image is determined by the updated gaze point coordinates.

[0041] According to an embodiment of the present application, if the current compression requirement is that the resolution of the compressed image remains unchanged, while obtaining the target compression rate curve, obtain the current compression center point coordinates;

[0042] The generating the first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter includes:

[0043] Generating the first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve and the current compression center point coordinates.

[0044] According to an embodiment of the present application, if the current compression requirement is that the resolution of the compressed image is determined by the updated gaze point coordinates, while obtaining the target compression rate curve, obtain the user's gaze point coordinates;

[0045] The generating the first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter includes:

[0046] Generating the first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve and the gaze point coordinates.

[0047] According to an embodiment of the present application, the compression module is specifically used for:

[0048] Using the first pixel coordinate mapping function to perform mapping compression on the horizontal and vertical pixel coordinates of the image to be compressed to obtain the compressed horizontal and vertical pixel coordinates;

[0049] Based on the correspondence relationship between the horizontal and vertical pixel coordinates of the image to be compressed and the horizontal and vertical pixel coordinates after compression, determine the color value of each pixel corresponding to the horizontal and vertical pixel coordinates after compression according to the color value of the pixel corresponding to the horizontal and vertical pixel coordinates of the image to be compressed;

[0050] Converge the color values of each pixel corresponding to the horizontal and vertical pixel coordinates after compression to obtain the compressed image.

[0051] According to an embodiment of the present application, the pixels on the compressed image correspond one-to-one with the pixels of the image to be compressed.

[0052] According to an embodiment of the present application, some of the pixels on the compressed image correspond one-to-one with the pixels of the image to be compressed, and the remaining pixels have no corresponding relationship with the pixels of the image to be compressed or the remaining pixels have a corresponding relationship with multiple pixels of the image to be compressed.

[0053] According to an embodiment of the present application, each point on the first pixel coordinate mapping function corresponds to a compression ratio value.

[0054] According to an embodiment of the present application, there are points on the first pixel coordinate mapping function that correspond to multiple compression ratio values.

[0055] According to an embodiment of the present application, after obtaining the compressed image, the compression module is further configured to:

[0056] Based on the second pixel coordinate mapping function, perform mapping decompression on the compressed image to obtain the image to be compressed.

[0057] According to the image compression device proposed in the embodiment of the present application, by obtaining the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed, the target compression rate curve can be determined according to the current compression requirement and the current compression rule, and the first pixel coordinate mapping function can be generated according to the target compression rate curve and the current variable rendering rate parameter. Based on the first pixel coordinate mapping function, perform mapping compression on the image to be compressed to obtain the compressed image. Thus, by using the pixel coordinate mapping function to compress the image, the problems of large consumption of computing resources and large storage space requirements and poor display effect of the compressed image during image compression at the present stage are solved, and the user's visual experience is improved.

[0058] To achieve the above object, an embodiment of the third aspect of the present application proposes an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the image compression method as described in the above embodiment.

[0059] In the fourth aspect of the present application, an embodiment provides a computer-readable storage medium, on which a computer program is stored, and the program is executed by a processor to implement the image compression method as described in the above embodiments.

[0060] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present application. Description of the Drawings

[0061] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0062] Figure 1 is a flowchart of an image compression method according to an embodiment of the present application;

[0063] Figure 2 is a schematic diagram of a target compression ratio curve according to an embodiment of the present application;

[0064] Figure 3 is a schematic diagram of a first pixel coordinate mapping function according to an embodiment of the present application;

[0065] Figure 4 is a schematic diagram of a first pixel coordinate mapping function after normalization of coordinates when the gaze point changes according to an embodiment of the present application;

[0066] Figure 5 is a schematic diagram of a target compression ratio curve after the gaze point changes according to an embodiment of the present application;

[0067] Figure 6 is a schematic diagram of a first pixel coordinate mapping function after the gaze point changes according to another embodiment of the present application;

[0068] Figure 7 is a schematic diagram of a target compression ratio curve after the gaze point changes according to another embodiment of the present application;

[0069] Figure 8 is a schematic diagram showing a target compression ratio curve and a variable rendering rate distribution curve of a graphics card in the same coordinate system according to an embodiment of the present application;

[0070] Figure 9 is a schematic diagram of a discontinuous first pixel coordinate mapping function according to an embodiment of the present application;

[0071] Figure 10 is a schematic diagram of a non-smooth first pixel coordinate mapping function according to an embodiment of the present application;

[0072] Figure 11 Schematic diagram of the first pixel coordinate mapping function after coordinate normalization according to an embodiment of the present application;

[0073] Figure 12 Schematic diagram of the first pixel coordinate mapping function asymmetrically varying along the gaze point coordinates according to an embodiment of the present application;

[0074] Figure 13 Schematic diagram of the first pixel coordinate mapping function when the compression curve patterns of the horizontal coordinate and the vertical coordinate are completely different according to an embodiment of the present application;

[0075] Figure 14 Schematic diagram of an image compression system according to an embodiment of the present application;

[0076] Figure 15 Schematic diagram of the actual compression effect according to an embodiment of the present application;

[0077] Figure 16 Block diagram of an image compression device according to an embodiment of the present application;

[0078] Figure 17 Schematic diagram of the structure of an electronic device according to an embodiment of the present application. Detailed Description of the Embodiment

[0079] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the drawings, in which the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0080] The image compression method, device, electronic device and storage medium according to the embodiments of the present application will be described below with reference to the drawings. First, the image compression method according to the embodiments of the present application will be described with reference to the drawings.

[0081] Before introducing the image compression method proposed by the embodiments of the present application, the background of its proposal will be briefly introduced.

[0082] Mixed Reality (MR) is a further development of virtual reality technology. This technology introduces real scene information into the virtual environment, builds an interactive feedback information loop between the virtual world, the real world and the user, and enhances the realism of the user experience. Based on mixed reality technology, mixed reality devices, as a form of the next generation of personal intelligent terminals, can bring people a new experience and convenience by combining virtual information with the real world. In the field of education, mixed reality devices can provide students with a more vivid and intuitive learning experience. For example, students can visit historical sites or participate in experiments through mixed reality devices to better understand and remember what they have learned; in the field of entertainment, mixed reality devices can bring people a more immersive gaming and entertainment experience. Players can interact with other players in the virtual world and experience unprecedented gaming fun; in the medical field, mixed reality devices can help doctors perform more precise surgery and treatment. Doctors can observe the internal structure of patients through mixed reality devices, so as to better perform surgical operations; in the field of work, mixed reality devices can provide employees with a more efficient and convenient way of working. Employees can remotely collaborate with colleagues through mixed reality devices to complete project tasks together. With the continuous development of technology, the application scope of mixed reality devices will continue to expand.

[0083] A head-mounted display device (Vision Pro) based on mixed reality technology came into being. In the interface of Vision Pro, users can place the screen in front of their eyes and adjust it freely within the field of view. In simple terms, the size and distance of the interface can be adjusted and its display can be expanded in the virtual space. 3D objects can also be projected into the real space. For example, if you want to buy furniture, you can pull it out and put it in the real space to try out the effect. It can be seen that high-quality compression of the picture has become an important technology of the multi-processor chip architecture.

[0084] Users are not sensitive to information about areas outside the gaze point, so the embodiment of the present application provides an image compression method based on the gaze point, which can effectively reduce the amount of image data, thereby reducing the requirements for bandwidth and storage space.

[0085] Figure 1 A flowchart of an image compression method provided in an embodiment of the present application.

[0086] For example, Figure 1 As shown, the image compression method comprises the following steps:

[0087] In step S101, the current compression requirement, the current compression rule, the current variable rendering rate parameter and the image to be compressed are obtained.

[0088] It can be understood that Variable Rate Rendering (VRR) is a technology for dynamically adjusting the rendering frame rate. This technology can improve image quality and reduce unnecessary rendering work. It dynamically adjusts the rendering frame rate by detecting the complexity or degree of dynamic change of the image. Current variable rate rendering parameters include frame rate control (the core parameter of VRR, used to dynamically adjust the rendering frame rate), rendering targets (such as pixel accuracy, object edges, level of detail, etc., and VRR can adopt different strategies to dynamically adjust the level of rendering detail for different rendering targets), perception thresholds (used to detect the complexity or degree of dynamic change of the image), etc. Current variable rate rendering parameters can be obtained through the graphics card GPU (Graphics Processing Unit). New types of graphics cards have the characteristic of variable rate rendering in different regions of the screen. Based on this characteristic, the rendering pixel accuracy of different regions of the screen can be adjusted by setting parameters.

[0089] In the application in the field of mixed reality, the image to be compressed can be a two-dimensional image generated by a computer from a digital three-dimensional scene. For example, in the embodiments of the present application, the image to be compressed is obtained through three-dimensional rendering by a graphics processing unit.

[0090] It should be noted that the source, format, or size of the image to be compressed in the embodiments of the present application is not limited in any way, as long as it can meet the application requirements.

[0091] Among them, in some embodiments, the current compression rule is to determine the non-compression region, and / or, the gradient compression region, and / or, the maximum compression region of the image to be compressed; among them, the non-compression region is a region with a first preset size corresponding to the current compression center point coordinates or the gaze point coordinates; the gradient compression region is a region with a second preset size adjacent to the non-compression region; the maximum compression region is the region of the image to be compressed except for the non-compression region and the gradient compression region.

[0092] Among them, both the first preset size and the second preset size can be preset by those skilled in the art, or obtained through a limited number of experiments, or obtained through a limited number of computer simulations. No specific limitation is made here.

[0093] It can be understood that the uncompressed area of the image to be compressed is the part of the image that is not compressed, which can also be called the "lossless area". This part of the area retains the original pixel information during the image compression process without data loss. Such areas usually exist in parts of the image with rich details or high contrast; the gradually compressed area of the image to be compressed is the part of the image that is compressed. In this part of the area, pixel information is lost during the image compression process, but enough details are still retained so that after decompression, the human eye can still perceive most of the original information. Such areas are usually used to retain the main content or details in the image; the maximum compressed area of the image to be compressed is the part of the image that is compressed the most severely. In this part of the area, a large amount of pixel information is lost during the image compression process, so that after decompression, the human eye may not be able to recognize the original image content. Such areas are usually for saving storage space or transmission bandwidth and do not pay too much attention to the quality after decompression.

[0094] Determining these three areas of the image to be compressed helps to better balance the compression quality and compression efficiency during the image compression process. For example, in order to maintain the quality of the image, the proportion of the maximum compressed area can be minimized as much as possible, while optimizing and adjusting the proportions of the gradually compressed area and the uncompressed area.

[0095] In some embodiments, the current compression requirement is the requirement that the resolution of the compressed image remains unchanged, or the requirement that the resolution of the compressed image is determined by the updated fixation point coordinates.

[0096] It can be understood that the current compression requirement refers to the actual requirement when the user compresses the image, that is, the user's requirement for the resolution of the compressed image, including that the resolution of the compressed image remains unchanged, that is, when the user's fixation point coordinates are updated, the resolution of the compressed image always remains unchanged; or the resolution of the compressed image is determined by the updated fixation point coordinates, that is, when the fixation point coordinates are updated, the resolution of the compressed image is determined by the updated fixation point coordinates.

[0097] In step S102, a target compression rate curve is determined according to the current compression requirement and the current compression rule, and a first pixel coordinate mapping function is generated according to the target compression rate curve and the current variable rendering rate parameter.

[0098] It can be understood that in the embodiments of the present application, the first pixel coordinate mapping function (i.e., the pixel coordinate mapping compression curve) is generally calculated on the CPU (Central Processing Unit) or the GPU. Based on the target compression rate curve and the current variable rendering rate parameter, etc., a unique fusion algorithm is adopted to obtain it under the balance of the picture quality and compression ratio of the original image. Considering the current variable rendering rate parameter can ensure that the first pixel coordinate mapping function better conforms to the characteristics of computer hardware.

[0099] The following will provide a detailed description of how to construct a pixel coordinate mapping function.

[0100] As a possible implementation, in some embodiments, if the current compression requirement is that the resolution of the compressed image remains unchanged, while obtaining the target compression rate curve, the current compression center point coordinates are obtained; a first pixel coordinate mapping function is generated according to the target compression rate curve and the current variable rendering rate parameter, including: generating a first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the current compression center point coordinates.

[0101] Among them, the current compression center point coordinates can be coordinate values preset by the user.

[0102] Specifically, if the current compression requirement is that the resolution of the compressed image remains unchanged, the target compression rate curve is determined according to the current compression requirement and the current compression rule. As Figure 2 shown, through reasonable design of the target compression rate curve, it can be ensured that during the process of the gaze point coordinates being updated and changing, the area formed by the target compression rate curve and the horizontal axis of the coordinate system remains unchanged. If, as the gaze point coordinates change, the area formed by the target compression rate curve and the horizontal axis of the coordinate system always remains unchanged, it indicates that the screen resolution of the compressed image will remain unchanged, thereby ensuring that the amount of data transmitted each time for the screen is the same.

[0103] After obtaining the current compression center point coordinates, the embodiments of the present application can generate a first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the current compression center point coordinates using related technical means (such as the NumPy library in Python or neural network model training), as Figure 3 shown, and no specific limitation is made here.

[0104] Optionally, in some other embodiments, if the current compression requirement is that the resolution of the compressed image is determined by the updated gaze point coordinates, while obtaining the target compression rate curve, the gaze point coordinates of the user are obtained; a first pixel coordinate mapping function is generated according to the target compression rate curve and the current variable rendering rate parameter, including: generating a first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the gaze point coordinates.

[0105] It can be understood that the gaze point coordinates of the user are not fixed values. They can be obtained by collecting the movement information of the user's eyes through an eye movement sensor, and based on the movement information of the user's eyes, through related technical means (such as image processing technology), an eye movement image sequence or eye movement data composed of key point information is obtained, and then calculated based on the eye movement data.

[0106] Specifically, if the current compression requirement is that the resolution of the compressed image is determined by the updated fixation point coordinates, the target compression rate curve can be determined according to the current compression requirement and the current compression rule (as Figure 2 shown), so that through the reasonable design of the target compression rate curve, when the fixation point coordinates are updated and changed, the area formed by the target compression rate curve and the horizontal axis of the coordinate system will change accordingly, and the picture resolution of the compressed image obtained thereby will change with the change of the fixation point coordinates.

[0107] After obtaining the user's fixation point coordinates, the embodiment of the present application can generate a first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the fixation point coordinates by using relevant technical means (such as the NumPy library in Python or neural network model training), as Figure 3 shown, which is not specifically limited herein.

[0108] It should be noted that, as Figures 4 - 7 shown, with the update of the fixation point coordinates, the target compression rate curve and the curve corresponding to the first pixel coordinate mapping function will also change accordingly.

[0109] Furthermore, Figure 8 FIG. is a schematic diagram showing the target compression rate curve and the current variable rendering rate rendering curve in the same coordinate system. As Figure 8 shown, the current variable rendering rate rendering curve is above the target compression rate curve, indicating that the fineness of the rendered picture is higher than the accuracy requirement of the compressed picture.

[0110] That is to say, other indicators in the mixed reality system will have a dependent relationship with the target compression rate curve before and after. For example, if the variable rendering rate rendering curve is closely attached above the target compression rate curve, the rendering computing power of the graphics card can be prevented from being wasted.

[0111] In step S103, based on the first pixel coordinate mapping function, the image to be compressed is mapped and compressed to obtain the compressed image.

[0112] That is to say, after obtaining the first pixel coordinate mapping function, the embodiment of the present application can perform mapping compression on the image to be compressed determined in step S101 based on the first pixel coordinate mapping function, and thus the compressed image can be obtained.

[0113] To facilitate those skilled in the art to further understand how to use the first pixel coordinate mapping function to perform mapping compression on the image to be compressed to obtain the compressed image, the following will be elaborated in detail with specific embodiments.

[0114] As a possible implementation method, in some embodiments, based on the first pixel coordinate mapping function, the image to be compressed is mapped and compressed to obtain a compressed image, including: using the first pixel coordinate mapping function to perform mapping compression on the horizontal and vertical pixel coordinates of the image to be compressed to obtain compressed horizontal and vertical pixel coordinates; based on the correspondence between the horizontal and vertical pixel coordinates of the image to be compressed and the compressed horizontal and vertical pixel coordinates, determining the color value of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates according to the color value of the pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed; aggregating the color values of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates to obtain a compressed image.

[0115] It can be understood that the pixel coordinate mapping relationship can be represented by the first pixel coordinate mapping function; in digital image processing, the color value of a pixel point is widely used in the representation and processing of images, and the color value of each pixel point can be represented by the binary values of the three components of red, green, and blue. The value range of each component can take integer values between 0 and 255, and the image compression process is achieved by changing the binary values of the pixel point color values.

[0116] Specifically, in the embodiments of the present application, the pixel coordinates of an image can be divided into horizontal (X) pixel coordinates and vertical (Y) pixel coordinates. The rule information of the picture compression is recorded by a pixel coordinate mapping function composed of horizontal and vertical coordinates. Based on the first pixel coordinate mapping function, the horizontal pixel coordinate (Xv) and vertical pixel coordinate (Yv) of the image to be compressed (v) can be mapped and compressed to obtain the horizontal pixel coordinate (Xr) and vertical pixel coordinate (Yr) of the compressed image (r). Based on the correspondence between the horizontal and vertical pixel coordinates of the image to be compressed and the compressed horizontal and vertical pixel coordinates, the color value of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates can be determined according to the color value of the pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed. Aggregate and store the color values of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates in a data structure, such as an array or a matrix. This process needs to pay attention to the order and format of the color value data to ensure the accuracy of subsequent processing and display. Convert the color value data stored in the data structure into an image format to obtain a compressed image.

[0117] Optionally, in some embodiments, the pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed.

[0118] It can be understood that, in order to prevent obvious compression stitching edges from appearing in the compressed image, the curve corresponding to the first pixel coordinate mapping function in the embodiments of the present application can be a continuous curve. That is, the pixel points of the compressed image and the pixel points of the image to be compressed are in one-to-one correspondence. In other words, each pixel point on the compressed image must have one and only one corresponding pixel point on the image to be compressed, that is, the position and color value of each pixel point remain unchanged before and after compression.

[0119] For example, assume that the set of all pixel points of the compressed image is A, and each pixel point of the compressed image is represented as A1, A2, A3... An in sequence. The set of all pixel points of the image to be compressed is B, and each pixel point of the image to be compressed is represented as B1, B2, B3... Bn in sequence. Then, when the first pixel coordinate mapping function is continuous, each pixel point A1, A2, A3... An on the compressed image corresponds one-to-one with each pixel point B1, B2, B3... Bn on the image to be compressed, that is, A1 corresponds to B1, A2 corresponds to B2... An corresponds to Bn.

[0120] Optionally, in some other embodiments, some pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed, and the remaining pixel points have no corresponding relationship with the pixel points of the image to be compressed or the remaining pixel points have corresponding relationships with multiple pixel points of the image to be compressed.

[0121] It can be understood that the curve corresponding to the first pixel coordinate mapping function in the embodiments of the present application can also be a non-continuous curve, such as Figure 9 as shown. Then, the pixel points of the compressed image and the pixel points of the image to be compressed are not in one-to-one correspondence. That is, some pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed, and the remaining pixel points have no corresponding relationship with the pixel points of the image to be compressed or the remaining pixel points have corresponding relationships with multiple pixel points of the image to be compressed. In other words, the remaining pixel points on the compressed image cannot find corresponding pixel points on the image to be compressed, or there are multiple corresponding pixel points on the image to be compressed for the remaining pixel points on the compressed image.

[0122] For example, when the first pixel coordinate mapping function is non-continuous, some pixel points (such as A1, A2, A3) on the compressed image correspond one-to-one with the pixel points (such as B1, B2, B3) of the image to be compressed, that is, A1 corresponds to B1, A2 corresponds to B2, A3 corresponds to B3. However, for the remaining pixel points (such as A4, A5, A6... An) on the compressed image, A4 cannot find any corresponding point among the pixel points (such as B1, B2, B3, B4, B5, B6... Bn) of the image to be compressed, or the remaining pixel point such as A5 has corresponding relationships with the pixel points such as B4, B5, B6 on the image to be compressed at the same time.

[0123] Optionally, in some embodiments, each point on the first pixel coordinate mapping function corresponds to a compression ratio value.

[0124] It can be understood that each point on the first pixel coordinate mapping function corresponds to a compression ratio value, indicating that the curve corresponding to the first pixel coordinate mapping function can be a smooth curve. That is to say, during the process of mapping and compressing the image to be compressed, the compression ratio of the image will not change suddenly, that is, the compression ratio changes continuously, so that there will be no obvious compression splicing edges in the compressed image.

[0125] Optionally, in some other embodiments, there are points on the first pixel coordinate mapping function that correspond to multiple compression ratio values.

[0126] It can be understood that there are points on the first pixel coordinate mapping function that correspond to multiple compression ratio values, indicating that the curve corresponding to the first pixel coordinate mapping function can also be a non-smooth curve. As Figure 10 shown, Figure 10 the positions of the boxes in Figure 10 are the positions where the compression ratio of the image changes suddenly. For example, the point at the position of the first box represents the compression ratio k1, the point at the position of the second box represents the compression ratio k2, the point at the position of the third box represents the compression ratio k3, and the point at the position of the fourth box represents the compression ratio k4, and k1≠k2, k3≠k4. That is to say, if there is a

[0127] such mutation as shown in

[0128] shown, it means that the compression ratio does not change continuously.

[0127] For the convenience of understanding by those skilled in the art, the following will be described with examples.

[0128] For example, in the embodiment of the present application, a certain dimension in the image to be compressed, such as 2000 pixels in width, is mapped to 1400 pixels. The first pixel coordinate mapping function on which the image to be compressed is based has the following characteristics: ① The pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed; ② The compression ratio changes continuously (that is, each point on the first pixel coordinate mapping function corresponds to a compression ratio value); ③ It changes symmetrically within a certain range along the center of the fixation point; ④ The size of the compressed picture does not change with the change of the fixation point; ⑤ The modes of the first pixel coordinate mapping functions of the horizontal coordinate and the vertical coordinate are the same. If the pixel coordinates of the image to be compressed are used as the horizontal axis and the pixel coordinates of the compressed image are used as the vertical axis, then the first pixel coordinate mapping function is as Figure 3 shown. This first pixel coordinate mapping function is represented in a segmented manner. In the embodiment of the present application, the formula (V0, V1, Vgaze, V2, V3) is used to represent the position of the segment points. After normalizing the coordinates, the first pixel coordinate mapping function is as Figure 11As shown in the figure. If the first pixel coordinate mapping function is continuous and smooth, then the pixels of the compressed image correspond one-to-one with the pixels of the image to be compressed, and the compression ratio changes continuously, which can avoid the problem of obvious compression splicing edges in different compression ratio regions of the compressed image and improve the user's visual experience.

[0129] In addition, while the gaze point is moving, the change of the compression ratio of the picture within a certain area around the gaze point can be kept symmetric and the resolution of the finally output picture remains unchanged. As Figure 11 shown in the first pixel coordinate mapping function after coordinate normalization, the range of the area where the gaze point can keep the compression ratio of the picture symmetrically changing and the resolution of the finally output picture remains unchanged is 0.15 - 0.85.

[0130] Of course, the first pixel coordinate mapping function can also change asymmetrically along the gaze point, as Figure 12 shown; the patterns of the first pixel coordinate mapping functions of the horizontal coordinate and the vertical coordinate can also be completely different, as Figure 13 shown, where Figure 13 (a) is a schematic diagram of the pixel coordinate mapping compression curve of the horizontal coordinate when the patterns of the first pixel coordinate mapping functions of the horizontal coordinate and the vertical coordinate are completely different in an embodiment of the present application, Figure 13 (b) is a schematic diagram of the pixel coordinate mapping compression curve of the vertical coordinate when the patterns of the first pixel coordinate mapping functions of the horizontal coordinate and the vertical coordinate are completely different in an embodiment of the present application. The characteristics of the first pixel coordinate mapping function can be set according to the actual needs of the user and are not specifically limited here.

[0131] In addition, in some embodiments, after obtaining the compressed image, it further includes: based on the second pixel coordinate mapping function, performing mapping decompression on the compressed image to obtain the image to be compressed.

[0132] Specifically, after obtaining the compressed image, the process of mapping and decompressing the compressed image is the inverse process of mapping and compressing the image to be compressed. That is, the horizontal pixel coordinate (Xr) of the compressed image can be used to obtain the horizontal pixel coordinate (Xv) of the image to be compressed according to the second pixel coordinate mapping function, and the vertical pixel coordinate (Yr) of the compressed image can be used to obtain the vertical pixel coordinate (Yv) of the image to be compressed according to the second pixel coordinate mapping function. The compressed image is mapped and decompressed according to the horizontal pixel coordinate (Xv) and the vertical pixel coordinate (Yv) of the image to be compressed. Based on the corresponding relationship between the horizontal and vertical pixel coordinates of the image to be compressed and the horizontal and vertical pixel coordinates of the compressed image, the color value of each pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed is determined according to the color value of the pixel point corresponding to the horizontal and vertical pixel coordinates of the compressed image. The color values of each pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed are aggregated and stored in a data structure, such as an array or a matrix. The color value data stored in the data structure is converted into an image format, and thus the image to be compressed can be obtained.

[0133] To facilitate those skilled in the art to further understand the image compression method proposed in the embodiments of the present application, the following will be further elaborated in conjunction with Figure 14 and Figure 15 for further elaboration.

[0134] As Figure 14 shown, Figure 14 is a schematic diagram of an image compression system according to another embodiment of the present application. The image compression method is combined with the image compression system. Among them, the image compression system includes: an eye movement sensor, an eye movement calculation unit, a graphics rendering unit, a pixel coordinate mapping function calculation unit, an image compression execution unit, an image transmission unit, an image receiving and decompression unit, and an image display unit.

[0135] Among them, the eye movement sensor is a sensor that collects the movement information of the human eye. According to the human eye movement information, it can output eye movement data composed of an eye movement image sequence or human eye key point information, and these data can be used as the input information of the eye movement calculation unit; the eye movement calculation unit can output the coordinate point information of the eye fixation point on the screen (i.e., the eye fixation point position parameter) according to the input eye movement data, and the eye fixation point position parameter will be input to the pixel coordinate mapping function calculation unit; the graphics rendering unit generally refers to the graphics card GPU. The new graphics card has the characteristic of variable rendering rate in different regions of the screen. Based on this characteristic, by setting parameters, the rendering pixel density of different regions of the screen can be adjusted. The rendering density of different regions in the screen can be represented by a formula or a curve. This part of information data (i.e., the current graphics card variable rendering rate distribution parameter) is also input to the pixel coordinate mapping compression curve calculation unit; the pixel coordinate mapping compression curve calculation unit generally performs calculations on the CPU or GPU. The input data of this unit includes the eye fixation point position parameter, the current lens optical parameter, and the current graphics card variable rendering rate distribution parameter. Using a unique fusion algorithm, when achieving a balance between the picture quality and the compression ratio, the preset pixel coordinate mapping function of the image to be compressed and the compressed image can be output; the image compression execution unit is generally also the graphics card GPU. The input data of this unit is the pixel coordinate mapping compression curve calculated by the pixel coordinate mapping compression curve calculation unit. This curve can be represented by a piecewise formula. In addition, the input data of the image compression execution unit also includes the image rendered by the graphics rendering unit, so as to output the compressed image to the image transmission unit; the image transmission unit outputs data in the transmission protocol format (i.e., the compressed image); the input of the image receiving and decompressing unit is the compressed image transmitted in the transmission protocol format. After the protocol decoding and image decompression of this unit, the image to be compressed after decompression and restoration is obtained and output to the image display unit; the image display unit displays the image to be compressed after decompression and restoration at the corresponding position to be displayed.

[0136] Further, as Figure 15 shown, Figure 15 (a) is a schematic diagram of the image to be compressed; Figure 15 (b) is a schematic diagram after compression according to the fixation point position in the upper right part and the lower left part by using the image compression method of the embodiment of the present application.

[0137] It should be noted that the method proposed in the embodiment of the present application can also be applicable to data transmission between multiple computing modules (such as graphics cards, display dedicated chips, CPUs, etc.), and has high applicability.

[0138] The image compression method proposed according to the embodiments of the present application can determine a target compression rate curve based on the current compression requirement and the current compression rule by obtaining the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed, and can generate a first pixel coordinate mapping function based on the target compression rate curve and the current variable rendering rate parameter. Based on the first pixel coordinate mapping function, the image to be compressed is mapped and compressed to obtain a compressed image. Thus, by using the pixel coordinate mapping function to compress the image, the problems of large consumption of computing resources and large storage space requirements during image compression at the present stage, and the poor display effect of the compressed image are solved, and the user's visual experience is improved.

[0139] Next, an image compression device proposed according to the embodiments of the present application will be described with reference to the accompanying drawings.

[0140] Figure 16 It is a block diagram of an image compression device according to an embodiment of the present application.

[0141] As Figure 16 shown, the image compression device 10 includes: an acquisition module 100, a generation module 200, and a compression module 300.

[0142] Among them, the acquisition module 100 is used to acquire the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed;

[0143] The generation module 200 is used to determine a target compression rate curve based on the current compression requirement and the current compression rule, and generate a first pixel coordinate mapping function based on the target compression rate curve and the current variable rendering rate parameter; and

[0144] The compression module 300 is used to perform mapping compression on the image to be compressed based on the first pixel coordinate mapping function to obtain a compressed image.

[0145] Further, in some embodiments, the current compression rule is to determine the non-compression area, and / or, the gradient compression area, and / or, the maximum compression area of the image to be compressed;

[0146] Among them, the non-compression area is an area of a first preset size corresponding to the current compression center point coordinates or the fixation point coordinates;

[0147] The gradient compression area is an area of a second preset size adjacent to the non-compression area;

[0148] The maximum compression area is the area of the image to be compressed except for the non-compression area and the gradient compression area.

[0149] Further, in some embodiments, the current compression requirement is a requirement for the resolution of the compressed image to remain unchanged, or a requirement for the resolution of the compressed image to be determined by the updated gaze point coordinates.

[0150] Further, in some embodiments, if the current compression requirement is for the resolution of the compressed image to remain unchanged, while obtaining the target compression rate curve, the current compression center point coordinates are obtained;

[0151] The generation module 200 is specifically configured to:

[0152] Generate a first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the current compression center point coordinates.

[0153] Further, in some embodiments, if the current compression requirement is for the resolution of the compressed image to be determined by the updated gaze point coordinates, while obtaining the target compression rate curve, the gaze point coordinates of the user are obtained;

[0154] The generation module 200 is specifically configured to:

[0155] Generate a first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the gaze point coordinates.

[0156] Further, in some embodiments, the compression module 300 is specifically configured to:

[0157] Use the first pixel coordinate mapping function to perform mapping compression on the horizontal and vertical pixel coordinates of the image to be compressed, obtaining the compressed horizontal and vertical pixel coordinates;

[0158] Based on the correspondence between the horizontal and vertical pixel coordinates of the image to be compressed and the compressed horizontal and vertical pixel coordinates, determine the color value of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates according to the color value of the pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed;

[0159] Converge the color values of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates to obtain the compressed image.

[0160] Further, in some embodiments, the pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed.

[0161] Further, in some embodiments, some pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed, and the remaining pixel points have no corresponding relationship with the pixel points of the image to be compressed or the remaining pixel points have a corresponding relationship with multiple pixel points of the image to be compressed.

[0162] Further, in some embodiments, each point on the first pixel coordinate mapping function corresponds to a compression rate value.

[0163] Further, in some embodiments, there are points corresponding to multiple compression ratio values on the first pixel coordinate mapping function.

[0164] Further, in some embodiments, after obtaining the compressed image, the compression module 300 is further configured to:

[0165] Based on the second pixel coordinate mapping function, perform mapping decompression on the compressed image to obtain the image to be compressed.

[0166] It should be noted that the foregoing explanation of the embodiments of the image compression method also applies to the image compression device of this embodiment, and will not be repeated here.

[0167] According to the image compression device provided by the embodiments of the present application, by obtaining the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed, the target compression rate curve can be determined according to the current compression requirement and the current compression rule, and the first pixel coordinate mapping function can be generated according to the target compression rate curve and the current variable rendering rate parameter. Based on the first pixel coordinate mapping function, perform mapping compression on the image to be compressed to obtain the compressed image. Thus, by using the pixel coordinate mapping function to compress the image, the problems of large consumption of computing resources and large storage space requirements, as well as poor display effects of the compressed image, during the current stage of image compression are solved, and the user's visual experience is improved.

[0168] Figure 17 It is a schematic structural diagram of an electronic device provided by the embodiments of the present application. The electronic device may include:

[0169] A memory 1701, a processor 1702, and a computer program stored on the memory 1701 and executable on the processor 1702.

[0170] When the processor 1702 executes the program, it implements the image compression method provided in the above embodiments.

[0171] Further, the electronic device further includes:

[0172] A communication interface 1703 for communication between the memory 1701 and the processor 1702.

[0173] The memory 1701 is used to store a computer program executable on the processor 1702.

[0174] The memory 1701 may include a high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0175] If the memory 1701, the processor 1702, and the communication interface 1703 are implemented independently, the communication interface 1703, the memory 1701, and the processor 1702 can be interconnected via a bus to complete communication with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 17 only a thick line is used in Figure 17 , but it does not mean that there is only one bus or one type of bus.

[0176] Optionally, in a specific implementation, if the memory 1701, the processor 1702, and the communication interface 1703 are integrated on a single chip, the memory 1701, the processor 1702, and the communication interface 1703 can complete communication with each other through an internal interface.

[0177] The processor 1702 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0178] The embodiments of the present application also provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the above image compression method is implemented.

[0179] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0180] In the description of this specification, references to the description of terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0181] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. An image compression method, characterized in that, Including the following steps: Obtain the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed; Determine the target compression rate curve according to the current compression requirement and the current compression rule, and generate a first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter; And Based on the first pixel coordinate mapping function, perform mapping compression on the image to be compressed to obtain a compressed image.

2. The method according to claim 1, characterized in that, The current compression rule is to determine the non-compression area, and / or the gradient compression area, and / or the maximum compression area of the image to be compressed; Wherein, the non-compression area is an area with a first preset size corresponding to the current compression center point coordinate or the fixation point coordinate; The gradient compression area is an area with a second preset size adjacent to the non-compression area; The maximum compression area is the area of the image to be compressed except the non-compression area and the gradient compression area.

3. The method according to claim 1, characterized in that The current compression requirement is the requirement that the resolution of the compressed image remains unchanged, or the requirement that the resolution of the compressed image is determined by the updated fixation point coordinate.

4. The method according to claim 3, characterized in that If the current compression requirement is that the resolution of the compressed image remains unchanged, while obtaining the target compression rate curve, obtain the current compression center point coordinate; The generating the first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter includes: Generating the first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the current compression center point coordinate.

5. The method according to claim 3, wherein If the current compression requirement is that the resolution of the compressed image is determined by the updated fixation point coordinate, while obtaining the target compression rate curve, obtain the user's fixation point coordinate; The generating the first pixel coordinate mapping function according to the target compression rate curve and the current variable rendering rate parameter includes: Generating the first pixel coordinate mapping function according to the current variable rendering rate parameter, the target compression rate curve, and the fixation point coordinate.

6. The method according to claim 1, wherein The performing mapping compression on the image to be compressed based on the first pixel coordinate mapping function to obtain a compressed image includes: Using the first pixel coordinate mapping function to perform mapping compression on the horizontal and vertical pixel coordinates of the image to be compressed to obtain the compressed horizontal and vertical pixel coordinates; Based on the correspondence between the horizontal and vertical pixel coordinates of the image to be compressed and the compressed horizontal and vertical pixel coordinates, determine the color value of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates according to the color value of the pixel point corresponding to the horizontal and vertical pixel coordinates of the image to be compressed; Converge the color values of each pixel point corresponding to the compressed horizontal and vertical pixel coordinates to obtain the compressed image.

7. The method according to any one of claims 1-6, characterized in that, The pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed.

8. The method according to any one of claims 1 to 6, characterized in that, Some pixel points on the compressed image correspond one-to-one with the pixel points of the image to be compressed, and the remaining pixel points have no corresponding relationship with the pixel points of the image to be compressed or the remaining pixel points have a corresponding relationship with multiple pixel points of the image to be compressed.

9. The method according to any one of claims 1-6, characterized in that, Each point on the first pixel coordinate mapping function corresponds to a compression ratio value respectively.

10. The method according to any one of claims 1-6, characterized in that, There are points on the first pixel coordinate mapping function that correspond to multiple compression ratio values.

11. The method according to claim 1, characterized in that, After obtaining the compressed image, it further includes: Based on the second pixel coordinate mapping function, performing mapping decompression on the compressed image to obtain the image to be compressed.

12. An image compression device, characterized in that, It includes: An acquisition module, configured to acquire the current compression requirement, the current compression rule, the current variable rendering rate parameter, and the image to be compressed; A generation module, configured to determine a target compression ratio curve according to the current compression requirement and the current compression rule, and generate a first pixel coordinate mapping function according to the target compression ratio curve and the current variable rendering rate parameter; And A compression module, configured to perform mapping compression on the image to be compressed based on the first pixel coordinate mapping function to obtain a compressed image.

13. An electronic device, characterized in that, It includes: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the image compression method according to any one of claims 1-11.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to be used for implementing the image compression method according to any one of claims 1-11.

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