Image processing method and device, equipment, storage medium and product
By dynamically adjusting image segmentation parameters based on image segmentation information, the problem of insufficient flexibility caused by fixed parameters in image processing is solved. This enables image processing using different segmentation information for different images, improving coding efficiency and adaptability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-24
- Publication Date
- 2026-03-24
AI Technical Summary
The existing image segmentation parameters are fixed in the third-generation audio and video coding standard, resulting in low flexibility in image processing.
By acquiring the image segmentation information of the image to be processed, custom or preset image segmentation can be performed according to the characteristics of different images. The storage location and method of image segmentation parameters can be dynamically adjusted, and different images can be processed using different image segmentation information.
It improves the flexibility of image processing, enabling it to adapt to rapidly changing content or scenarios, and enhances coding efficiency and image processing adaptability.
Smart Images
Figure CN121728256A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data processing technology, and in particular to image processing methods, apparatus, devices, storage media and products. Background Technology
[0002] Image partitioning structure, as the foundation of the coding framework, has a significant impact on coding performance. Among them, slices and tiles are two core image partitioning tools, and their design concepts and technical implementations are constantly evolving. The third-generation audio-visual coding standard (AVS3) uses the patch method for image partitioning. However, the existing AVS3 patch mechanism suffers from fixed partitioning parameters; that is, the size and number of AVS3 patches are defined in the sequence header, and the entire sequence must use the same set of parameters, resulting in low flexibility in image processing. Summary of the Invention
[0003] The main objective of this application is to provide an image processing method, apparatus, device, storage medium, and product, which aims to solve the existing technical problem of fixed image segmentation parameters.
[0004] To achieve the above objectives, this application proposes an image processing method, which includes: Obtain image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; Image processing is performed on the image to be processed based on the image segmentation information.
[0005] Optionally, the image processing of the image to be processed based on the image segmentation information includes: If the image segmentation method is a custom segmentation method, obtain the storage location of the image segmentation parameters; The image segmentation parameters are obtained based on the storage location; Image processing is performed on the image to be processed according to the image segmentation parameters.
[0006] Optionally, the image segmentation parameters are stored at the frame header position of the image to be processed.
[0007] Optionally, the image processing of the image to be processed based on the image segmentation information includes: When the image segmentation method is to follow the previous frame segmentation method, the image segmentation parameters of the previous frame image are obtained; Image processing is performed on the image to be processed according to the image segmentation parameters.
[0008] Optionally, the image processing of the image to be processed based on the image segmentation information includes: When the image segmentation method is the default segmentation method, obtain the preset image segmentation parameters corresponding to the image to be processed; Image processing is performed on the image to be processed based on the preset image segmentation parameters.
[0009] Optionally, obtaining the image segmentation information corresponding to the image to be processed includes: Determine the image type of the image to be processed; The image segmentation information of the image to be processed is determined based on the image type.
[0010] Furthermore, to achieve the above objectives, this application also proposes an image processing apparatus, the image processing apparatus comprising: The acquisition module is used to acquire image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; An image processing module is used to perform image processing on the image to be processed based on the image segmentation information.
[0011] In addition, to achieve the above objectives, this application also proposes an image processing apparatus, the apparatus comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the image processing method as described above.
[0012] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the image processing method described above.
[0013] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the image processing method described above.
[0014] This application obtains image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; and performs image processing on the image to be processed based on the image segmentation information. Because this application processes the image according to the image segmentation method corresponding to the image to be processed, compared to existing methods that use uniform image segmentation information for image processing, the above method of this application can achieve the goal of using different image segmentation information for image processing of different images, improving the flexibility of image processing. Attached Figure Description
[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a flowchart illustrating an embodiment of the image processing method of this application. Figure 2 This is a flowchart illustrating Embodiment 2 of the image processing method of this application; Figure 3 This is a schematic diagram comparing the coding performance of the image processing method in Embodiment 2 of this application; Figure 4 This is a schematic diagram of the module structure of the image processing device according to an embodiment of this application; Figure 5 This is a schematic diagram of the device structure of the hardware operating environment involved in the image processing method in the embodiments of this application.
[0018] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0019] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.
[0020] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.
[0021] The main solution of this application embodiment is: to obtain image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; and to perform image processing on the image to be processed based on the image segmentation information. Since this application processes the image to be processed according to the image segmentation method corresponding to the image to be processed, compared to existing methods that use uniform image segmentation information for image processing, the above method of this application can achieve the goal of using different image segmentation information for image processing of different images, improving the flexibility of image processing.
[0022] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device or image processing device capable of performing the above functions. The following description uses an image processing device as an example to illustrate this embodiment and the subsequent embodiments.
[0023] Based on this, embodiments of this application provide an image processing method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the image processing method of this application.
[0024] In this embodiment, the image processing method includes the following steps: Step S10: Obtain image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; It should be noted that the sub-images after image processing (segmentation) in this embodiment are patches in the AVS3 environment, and correspond to tiles or rectangular slices in other standards. The image to be processed can be a single image that needs to be encoded, or a frame image in a video stream that needs to be encoded. The image segmentation information can be the image segmentation method used when encoding and decoding the image to be processed. The image segmentation method in this embodiment can include a custom segmentation method, such as the user defining whether the image segmentation is regular or irregular according to their needs, as well as information such as the length and width of the sub-image blocks obtained after segmentation. Regular segmentation can mean that the length and width of the sub-image blocks are all the same, while irregular segmentation can mean that the length and width of the sub-image blocks are different, which can be completely different or partially different.
[0025] Step S20: Perform image processing on the image to be processed based on the image segmentation information.
[0026] It should be noted that the image processing of the image to be processed based on the image segmentation information can be divided into image processing during the encoding process and image processing during the decoding process. During the encoding process, image processing of the image to be processed based on the image segmentation information can involve dividing the image to be processed according to the image segmentation method corresponding to the image segmentation information to obtain multiple sub-image blocks. During the decoding process, the image to be processed can be multiple sub-image blocks obtained after dividing the original image, and image processing of the image to be processed based on the image segmentation information can involve decoding these multiple sub-image blocks according to the image segmentation method corresponding to the image segmentation information to obtain the original image.
[0027] Furthermore, in order to improve the flexibility of image processing, step S30 may include: when the image segmentation method is to follow the forward frame segmentation method, obtaining the image segmentation parameters of the previous frame image; Image processing is performed on the image to be processed according to the image segmentation parameters.
[0028] It should be noted that the aforementioned forward frame segmentation method can be to use the same segmentation method as the previous frame for image segmentation. This segmentation method is suitable for scenarios where the image to be processed is a single image frame in a video. The image segmentation parameters of the previous frame can be the image segmentation parameters of the previous frame of the image to be processed in the video stream.
[0029] Furthermore, in order to save the amount of encoded data, step S30 may include: when the image segmentation method is the default segmentation method, obtaining the preset image segmentation parameters corresponding to the image to be processed; Image processing is performed on the image to be processed based on the preset image segmentation parameters.
[0030] It should be noted that the default partitioning method can be a default image partitioning parameter defined for a batch of images or one or more video streams, i.e., the preset image partitioning parameter. Subsequently, for each frame in that batch of images or video stream, unless a forward frame partitioning or a custom partitioning is defined, the default image partitioning parameter will be used for image processing. This default image partitioning parameter can be stored in the sequence header of the video stream or in other locations.
[0031] In practical implementation, this embodiment allows dynamic modification of the patch partitioning parameters defined in the sequence header within the frame header. This achieves the goal of using different sub-image partitions for different frames. Specifically: 1. A default sub-image partitioning method can be defined in the sequence header, i.e., a default partitioning method can be defined; 2. Add a "frame-level sub-image partitioning flag" to the frame header, for example, a 2-bit flag; If the "frame-level sub-image partitioning flag" is set to "new partitioning" (e.g., 0b10), indicating a custom partitioning, then the definition of a new sub-image partitioning begins. The custom partitioning method for the current frame includes: regular mode: necessary parameters such as the number of slice rows / columns / width / height, starting address / scanning order, etc.; and irregular mode: descriptions of the number of slices, slice position / shape (e.g., a rectangular list or a sparse index map). The advantages of this partitioning method are: it provides sufficient flexibility, supporting unique sub-image partitioning methods for each frame to adapt to rapidly and significantly changing content / scenes, thereby improving coding efficiency. The disadvantages are: sub-image partitioning, especially complex sub-image partitioning, consumes a certain amount of encoded data; and the encoder needs to add frame-level decision logic to select when to enable the "new partitioning," which increases the implementation complexity of the encoder.
[0032] If the "frame-level sub-image partitioning flag" is set to reuse the current partitioning (e.g., 0b01), meaning the previous frame partitioning is used, then there is no need to define a new sub-image partitioning; instead, the partitioning used in the previous frame is reused. The advantages of this partitioning method are: extremely low bit overhead (relative to a new partitioning), the ability to reuse partitioning across multiple frames to improve parallel efficiency and implementation simplicity when the scene is stable, and the ability to maintain consistent task splitting within a GOP. The disadvantages are: if the content or scene changes significantly, inheriting the old partitioning may cause a localized decrease in efficiency; and failure and fallback strategies must be designed for random access or scene switching points.
[0033] If the "frame-level sub-image partitioning flag" is set to use the default partitioning (e.g., 0b00), then there is no need to define a new sub-image partitioning; instead, the default sub-image partitioning in the sequence header is used. The advantages of this partitioning method are: lowest bit overhead and simplest implementation; guaranteed consistency across the entire sequence partitioning, facilitating parallel processing and error isolation; and friendliness to random access and hardware pipelines. The disadvantages are: lack of adaptability to different content / frame types; and the potential for localized coding performance degradation when scene or texture complexity changes significantly due to fixed parameters.
[0034] In this embodiment, the above-described method allows for the selection of a suitable sub-image partitioning method from the sequence header, the preceding frame, and the new partition for a new encoded frame. The first two methods require only a 2-bit increase, while the latter provides sufficient flexibility for personalized sub-image partitioning. Furthermore, this partitioning can be inherited in subsequent frames by "inheriting the current partitioning." This approach achieves a balance between sequence-level consistency and frame-level flexibility, improving compression efficiency and adaptability with minimal changes to the bitstream structure.
[0035] This embodiment obtains image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; image processing is performed on the image to be processed based on the image segmentation information. Since this embodiment processes the image according to the image segmentation method corresponding to the image to be processed, compared to existing methods that use uniform image segmentation information for image processing, this embodiment can achieve the goal of using different image segmentation information for different images, improving the flexibility of image processing.
[0036] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of the image processing method of this application. Step S20 further includes the following steps: Step S201: If the image segmentation method is a custom segmentation method, obtain the storage location of the image segmentation parameters; It should be noted that the custom partitioning method allows users to define the partitioning method for each frame of the image based on the image category or image partitioning requirements. The image partitioning parameters may include whether the image is partitioned regularly or irregularly, and may also include information such as the length, width, or number of the partitioned sub-image blocks. The image partitioning parameters may be stored in the frame header of each image frame (such as in the frame header of the image to be processed), or they may be stored in other locations; this embodiment does not impose any restrictions on this.
[0037] Step S202: Obtain the image segmentation parameters based on the storage location; It should be noted that the image segmentation parameters can be obtained through the storage location of the image segmentation parameters. In this embodiment, a "frame-level sub-image segmentation flag," such as a 2-bit flag, can be added to the frame header to indicate the current image segmentation method. Alternatively, the image segmentation parameters can be stored in the frame header or in other locations; this embodiment does not impose any restrictions. If the image segmentation parameters are stored in other locations, after determining that the image segmentation method is a custom segmentation method based on the frame-level sub-image segmentation flag, the image segmentation parameters can be obtained according to the storage location.
[0038] This embodiment proposes a "two-layer control". That is, the partitioning method can be stored in two layers, such as the sequence header and the frame header. Custom partitioning and the use of the forward frame partitioning can be stored in the frame header, and the default partitioning can be stored in the sequence header. This can more clearly define the sequence header-frame header collaborative control system. Two-layer control is a method to balance frame-level flexibility and not significantly increase bits; it is also the main difference from single-layer (sequence layer or frame layer) control.
[0039] Step S203: Perform image processing on the image to be processed according to the image segmentation parameters.
[0040] It should be noted that the image processing of the image to be processed according to the image segmentation parameters can refer to step S30 in the above embodiment, and will not be repeated here.
[0041] Furthermore, in order to enable different sub-image segmentation methods for different frame types, this embodiment also includes: determining the image type of the image to be processed; The image segmentation information of the image to be processed is determined based on the image type.
[0042] It should be noted that in video encoding, to maximize data compression, not every frame stores a complete image. Video is decomposed into three different types of frames: intra-coded frames / keyframes (I-frames), forward prediction frames (P-frames), and bidirectional prediction frames (B-frames). The image type can include I-frames, P-frames, and B-frames. Determining the image segmentation information of the image to be processed based on the image type can be done by determining the corresponding image segmentation information according to the image type, for example: setting different sub-image segmentations for I-frames and P-frames. The sub-image segmentation method for P-frames is defined in the sequence header; a "frame-level sub-image segmentation flag" is defined in the header of intra-coded frames (I-frames) as the new segmentation; and a "frame-level sub-image segmentation flag" is defined in the header of inter-coded frames (P-frames and B-frames) to use the default segmentation. This allows for the use of different sub-image segmentations for different frame types with only a very small increase in bits. Although I-frames increase the number of bits due to the defined new segmentation, because I-frames are relatively few in number throughout the entire encoding sequence, this increase in data volume will not affect the overall encoding output bitrate. In this embodiment, smaller sub-image segmentation rules can be used in I-frames, while P / B frames follow the sequence-uniform segmentation to control complexity and bit rate.
[0043] Furthermore, a separate fixed sub-image partitioning method can be used for a video segment with a fixed scene. When the scene changes or enters a specific scene, a new partitioning method adapted to that scene can be defined in a certain frame using a "frame-level sub-image partitioning flag". Then, in subsequent frames, the "frame-level sub-image partitioning flag" can be used to reuse the current partitioning method, without having to define an independent partitioning method for each frame, thus saving the amount of encoded data.
[0044] It should be understood that in this embodiment, a sub-image is defined as a Patch in the AVS3 standard, a rectangular strip in the H.266 standard, or a Tile in the H.265 standard. This is a concept at a different level from the block partitioning strategy of the Coding Unit (CU) in video coding standards. A Coding Unit is a 64x64 or 128x128 pixel block, belonging to the micro-level partitioning within a Coding Tree Unit (CTU), serving the prediction and transformation process. A Patch, on the other hand, is a collection of several Coding Units constituting a rectangular region. It is the macro-level partitioning structure of the image, used to control the organization of the coding framework (such as Slice / Tile / Patch), rather than a specific prediction or transformation block. Therefore, this embodiment differs from the optimization of coding block partitioning; instead, it implements a frame-level adaptive sub-image partitioning mechanism under the coding framework, solving the problem of insufficient flexibility in high-level image partitioning.
[0045] For reference Figure 3 , Figure 3 This is a schematic diagram comparing the encoding performance of the image processing method in Embodiment 2 of this application; ULL_V3 represents the encoding performance of AVS3 encoder version v3 without sub-image partitioning; ULL_V3_Patch represents the encoding result according to the fixed sub-image partitioning method (i.e., image partitioning method) for all frames; Adaptive Patch represents the encoding result of using different sub-image partitioning for I-frames and PB-frames. It can be seen that the adaptive partitioning method can effectively solve the problem of significant performance degradation in certain sequences of the current AVS3 sub-image mode.
[0046] In this embodiment, when the image segmentation method is a custom segmentation method, the storage location of the image segmentation parameters is obtained; the image segmentation parameters are obtained based on the storage location; and image processing is performed on the image to be processed according to the image segmentation parameters. This embodiment performs image processing on the image to be processed according to the image segmentation method corresponding to the image to be processed, supporting a unique image segmentation method for each frame, which can adapt to rapidly and significantly changing content or scenes, thereby improving coding efficiency.
[0047] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the image processing method of this application. Any simple modifications based on this technical concept are within the protection scope of this application.
[0048] This application also provides an image processing apparatus, please refer to... Figure 4 The image processing apparatus includes: The acquisition module 10 is used to acquire image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; Image processing module 20 is used to perform image processing on the image to be processed based on the image segmentation information.
[0049] This embodiment obtains image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; image processing is performed on the image to be processed based on the image segmentation information. Since this embodiment processes the image according to the image segmentation method corresponding to the image to be processed, compared to existing methods that use uniform image segmentation information for image processing, this embodiment can achieve the goal of using different image segmentation information for different images, improving the flexibility of image processing.
[0050] The image processing apparatus provided in this application, employing the image processing method described in the above embodiments, can solve the existing technical problem of fixed image segmentation parameters. Compared with the prior art, the beneficial effects of the image processing apparatus provided in this application are the same as those of the image processing method described in the above embodiments, and other technical features in the image processing apparatus are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.
[0051] This application provides an image processing apparatus, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the image processing method in Embodiment 1 above.
[0052] The following is for reference. Figure 5 This document illustrates a structural schematic diagram of an image processing device suitable for implementing embodiments of this application. The image processing device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 5The image processing device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.
[0053] like Figure 5 As shown, the image processing device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the image processing device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the image processing device to communicate wirelessly or wiredly with other devices to exchange data. Although the figure shows an image processing device with various systems, it should be understood that it is not required to implement or possess all of the systems shown. More or fewer systems may be implemented alternatively.
[0054] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.
[0055] The image processing device provided in this application, employing the image processing method described in the above embodiments, can solve the existing technical problem of fixed image segmentation parameters. Compared with the prior art, the beneficial effects of the image processing device provided in this application are the same as those of the image processing method described in the above embodiments, and other technical features of the image processing device are the same as those disclosed in the previous embodiment method, and will not be repeated here.
[0056] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.
[0057] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0058] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to perform the image processing method described in the above embodiments.
[0059] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.
[0060] The aforementioned computer-readable storage medium may be included in an image processing device or may exist independently without being assembled into an image processing device.
[0061] Computer program code for performing the operations of this application can be written in one or more programming languages or a combination thereof. These programming languages include object-oriented programming languages—such as Python, Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0062] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0063] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.
[0064] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described image processing method, thereby solving the technical problem of fixed image segmentation parameters in existing technologies. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the image processing method provided in the above embodiments, and will not be repeated here.
[0065] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the image processing method described above.
[0066] The computer program product provided in this application can solve the technical problem of fixed image segmentation parameters in existing technologies. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the image processing method provided in the above embodiments, and will not be repeated here.
[0067] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.
Claims
1. An image processing method, characterized in that, The image processing method includes the following steps: Obtain image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; Image processing is performed on the image to be processed based on the image segmentation information.
2. The image processing method as described in claim 1, characterized in that, The image processing based on the image segmentation information includes: If the image segmentation method is a custom segmentation method, obtain the storage location of the image segmentation parameters; The image segmentation parameters are obtained based on the storage location; Image processing is performed on the image to be processed according to the image segmentation parameters.
3. The image processing method as described in claim 2, characterized in that, The image segmentation parameters are stored at the frame header position of the image to be processed.
4. The image processing method as described in claim 1, characterized in that, The image processing based on the image segmentation information includes: When the image segmentation method is to follow the previous frame segmentation method, the image segmentation parameters of the previous frame image are obtained; Image processing is performed on the image to be processed according to the image segmentation parameters.
5. The image processing method as described in claim 1, characterized in that, The image processing based on the image segmentation information includes: When the image segmentation method is the default segmentation method, obtain the preset image segmentation parameters corresponding to the image to be processed; Image processing is performed on the image to be processed based on the preset image segmentation parameters.
6. The image processing method according to any one of claims 1-5, characterized in that, The step of obtaining the image segmentation information corresponding to the image to be processed includes: Determine the image type of the image to be processed; The image segmentation information of the image to be processed is determined based on the image type.
7. An image processing apparatus, characterized in that, The image processing device includes: The acquisition module is used to acquire image segmentation information corresponding to the image to be processed, wherein the image segmentation information is used to identify the image segmentation method corresponding to the image to be processed; An image processing module is used to perform image processing on the image to be processed based on the image segmentation information.
8. An image processing device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the image processing method as described in any one of claims 1 to 6.
9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the image processing method as described in any one of claims 1 to 6.
10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of the image processing method as described in any one of claims 1 to 6.