Image signal processing self-checking system, method, equipment and medium

Abstract

The invention discloses an image signal processing self-checking system, method and device and a medium, and relates to the technical field of image processing, and the system comprises an algorithm data area mapping module which is used for establishing a mapping relation between an output data area memory and a self-checking data area memory; the self-checking area data management module is used for caching the output area data to a self-checking data area memory, judging whether the self-checking data area memory reaches a preset threshold value or not, and outputting the self-checking area data if the self-checking data area memory reaches the preset threshold value; the color space unification module is used for analyzing and calculating the self-inspection area data to obtain data area features, and analyzing the data area features by using a color space analysis model to obtain an analysis result; the difference analysis module is used for carrying out difference analysis on the analysis results to obtain difference information; and the self-checking module is used for determining an exception type and carrying out exception calculation on the difference analysis module according to the exception type so as to complete self-checking. The image signal processing self-checking and module debugging process can be simplified, and the image signal processing self-checking efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and particularly relates to an image signal processing self-check system, method, device and medium. Background Art

[0002] ISP (Image signal processing) is mainly used to process the output signal of the front-end image sensor. Specifically, the image processing process includes corrections in various aspects such as color, brightness, and geometry. In fact, whether for software or hardware, during the development of ISP, since each module directly affects the finally output image data, it is necessary to manually check each module, and the debugging process is cumbersome and complex.

[0003] As can be seen from the above, how to simplify the self-check of image signal processing and the module debugging process and improve the efficiency of self-check of image signal processing is a problem to be solved in this field. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide an image signal processing self-check system, method, device and medium, which can simplify the self-check of image signal processing and the module debugging process and improve the efficiency of self-check of image signal processing. The specific scheme is as follows:

[0005] In the first aspect, the present application discloses an image signal processing self-check system, including:

[0006] An algorithm data area mapping module, configured to establish a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module;

[0007] A self-check area data management module, configured to cache the output area data in the output data area memory to the self-check data area memory based on the mapping relationship, and determine whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, output the self-check area data;

[0008] A color space unification module, configured to parse and calculate the self-check area data to obtain data area features, and analyze the data area features using a preset color space analysis model to obtain an analysis result;

[0009] A difference analysis module, configured to perform difference analysis on the analysis result to obtain difference information;

[0010] A self-check module, configured to determine the abnormal type based on the difference information, and perform abnormal calculation on the difference analysis module according to the abnormal type to complete the self-check.

[0011] Optionally, the image signal processing self-check system further includes:

[0012] A parameter loading module for loading scene configuration parameters and image sensor configuration parameters for image signal processing;

[0013] An initialization and execution module for initializing the pipeline state machine to obtain the initialized pipeline state machine and executing the initialized pipeline state machine.

[0014] Optionally, the self-check area data management module includes:

[0015] A data enqueue cache module for obtaining the Mobile Industry Processor Interface data sent by the initialized pipeline state machine and obtaining the output area data in the output data area memory, and caching the Mobile Industry Processor Interface data and the output area data to the local self-check data area memory based on the mapping relationship;

[0016] A judgment module for judging whether the self-check data area memory reaches the preset threshold;

[0017] A data dequeue module for outputting self-check area data if the self-check data area memory reaches the preset threshold.

[0018] Optionally, the color space unification module includes:

[0019] A parsing and evaluation module for parsing the information header of the self-check area data to obtain a parsing result and evaluating the data validity of the parsing result;

[0020] A calculation module for calculating the self-check area data to obtain the data area features if the data validity evaluation passes;

[0021] An analysis module for analyzing the data area features using the color space analysis model to obtain the analysis result.

[0022] Optionally, the difference analysis module includes:

[0023] A color difference analysis and statistics module for performing color difference analysis and statistics on the analysis result to obtain color difference information;

[0024] A brightness difference analysis and statistics module for performing brightness difference analysis and statistics on the analysis result to obtain brightness difference information;

[0025] A shape difference analysis and statistics module for performing shape difference analysis and statistics on the analysis result to obtain shape difference information;

[0026] An edge difference analysis and statistics module, which is used to perform edge difference analysis and statistics on the analysis results to obtain edge difference information;

[0027] A difference information determination module, which is used to determine the difference information based on the color difference information, the brightness difference information, the shape difference information, and the edge difference information.

[0028] Optionally, the self-check module includes:

[0029] A color difference self-check module, which is used to perform abnormal calculation on the color difference analysis and statistics module according to the abnormal type to complete the color difference self-check;

[0030] A brightness difference self-check module, which is used to perform abnormal calculation on the brightness difference analysis and statistics module according to the abnormal type to complete the brightness difference self-check;

[0031] A shape difference self-check module, which is used to perform abnormal calculation on the shape difference analysis and statistics module according to the abnormal type to complete the shape difference self-check;

[0032] An edge difference self-check module, which is used to perform abnormal calculation on the edge difference analysis and statistics module according to the abnormal type to complete the edge difference self-check.

[0033] Optionally, the image signal processing self-check system further includes:

[0034] A queue detection module, which is used to detect whether there is still unprocessed self-check area data in the self-check data area of the self-check area data management module;

[0035] A jump module, which is used to jump to the step of parsing and calculating the unprocessed self-check area data by using the color space unification module if there is still unprocessed self-check area data in the self-check data area until there is no unprocessed self-check area data in the self-check data area.

[0036] In a second aspect, the present application discloses an image signal processing self-check method, including:

[0037] Establishing a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module through the algorithm data area mapping module;

[0038] Caching the output area data in the output data area memory to the self-check data area memory through the self-check area data management module and based on the mapping relationship, determining whether the self-check data area memory reaches a preset threshold, and if the self-check data area memory reaches the preset threshold, outputting the self-check area data;

[0039] The data in the self-check area is parsed and calculated by the color space unification module to obtain the characteristics of the data area, and the preset color space analysis model is used to analyze the characteristics of the data area to obtain the analysis result;

[0040] The difference analysis module performs difference analysis on the analysis result to obtain the difference information;

[0041] The self-check module determines the abnormal type based on the difference information, and performs abnormal calculation on the difference analysis module according to the abnormal type to complete the self-check.

[0042] In a third aspect, the present application discloses an electronic device, including:

[0043] A memory for storing a computer program;

[0044] A processor for executing the computer program to implement the foregoing image signal processing self-check method.

[0045] In a fourth aspect, the present application discloses a computer storage medium for storing a computer program; wherein, when the computer program is executed by a processor, the steps of the foregoing disclosed image signal processing self-check method are implemented.

[0046] It can be seen that the present application provides an image signal processing self-check system, including an algorithm data area mapping module for establishing a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module; a self-check area data management module for caching the output area data in the output data area memory to the self-check data area memory based on the mapping relationship, and determining whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, self-check area data is output; a color space unification module for parsing and calculating the self-check area data to obtain data area features, and analyzing the data area features using a preset color space analysis model to obtain an analysis result; a difference analysis module for performing difference analysis on the analysis result to obtain difference information; a self-check module for determining an abnormal type based on the difference information, and performing abnormal calculation on the difference analysis module according to the abnormal type to complete self-check. The present application caches the output area data to the self-check data area memory using the mapping relationship between the output data area memory of each module and the self-check data area memory in the self-check area data management module. If the self-check data area memory reaches the preset threshold, the self-check area data is parsed and calculated to obtain data area features, and the data area features are analyzed and differentially analyzed using a color space analysis model to obtain a difference type, thereby obtaining an abnormal type for abnormal inference and completing self-check. The present application can automatically implement the evaluation and self-check of each module in the image signal processing self-check system, simplify the image signal processing self-check and module debugging process, and can efficiently and quickly locate the abnormal algorithm module, improving the efficiency of image signal processing self-check. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained according to the provided drawings.

[0048] Figure 1 It is a schematic structural diagram of an image signal processing self-check system disclosed in the present application;

[0049] Figure 2 It is a flowchart of an image signal processing self-check method disclosed in the present application;

[0050] Figure 3 It is a flowchart of a specific image signal processing self-check method disclosed in the present application;

[0051] Figure 4 It is a schematic structural diagram of an electronic device provided by the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] The ISP is mainly used to process the output signals of the front-end image sensor. Specifically, the image processing process includes corrections in aspects such as color, brightness, and geometry. In fact, whether for software or hardware, during the development of the ISP, since each module directly affects the final output image data, it is necessary to manually check each module, and the debugging process is cumbersome and complex. As can be seen from the above, how to simplify the self-check and module debugging process of image signal processing and improve the efficiency of self-check of image signal processing is a problem to be solved in the art.

[0054] See Figure 1 As shown, the embodiment of the present application discloses an image signal processing self-check system, including:

[0055] An algorithm data area mapping module 11, configured to establish a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module;

[0056] A self-check area data management module 12, configured to cache the output area data in the output data area memory to the self-check data area memory based on the mapping relationship, and determine whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, output the self-check area data;

[0057] A color space unification module 13, configured to parse and calculate the self-check area data to obtain data area features, and analyze the data area features using a preset color space analysis model to obtain an analysis result;

[0058] A difference analysis module 14, configured to perform difference analysis on the analysis result to obtain difference information;

[0059] A self-check module 15, configured to determine the type of abnormality based on the difference information, and perform abnormality calculation on the difference analysis module according to the type of abnormality to complete self-check.

[0060] In this embodiment, the image signal processing self-check system is characterized by further comprising: a parameter loading module 16, configured to load the scene configuration parameters and image sensor configuration parameters of the image signal processing; an initialization and execution module 17, configured to perform an initialization operation on the pipeline state machine to obtain the initialized pipeline state machine and execute the initialized pipeline state machine. The parameter loading module 16 loads the ISP scene configuration parameters and the configuration parameters of the Sensor (image sensor), including the setting of the difference threshold and the memory threshold of the self-check area, etc.; the initialization and execution module 17 performs an initialization operation on the pipeline state machine to complete the system initialization.

[0061] In this embodiment, the self-check area data management module 12 includes: a data enqueue buffer module 121, configured to obtain the Mobile Industry Processor Interface data sent by the initialized pipeline state machine, obtain the output area data in the output data area memory, and cache the Mobile Industry Processor Interface data and the output area data to the local self-check data area memory based on the mapping relationship; a judgment module 122, configured to judge whether the self-check data area memory reaches the preset threshold; a data dequeue module 123, configured to output the self-check area data if the self-check data area memory reaches the preset threshold. That is, the data enqueue buffer module 121 queues the self-check data, including the data at the Pipeline (pipeline state machine) entrance and the output area data of each algorithm module; the data dequeue module 123 dequeues the self-check area data, that is, outputs the self-check area data.

[0062] In this embodiment, the color space unification module 13 includes: a parsing and evaluation module 131, configured to parse the information header of the self-check area data to obtain a parsing result and evaluate the data validity of the parsing result; a calculation module 132, configured to calculate the self-check area data to obtain the data area features if the data validity evaluation passes; an analysis module 133, configured to analyze the data area features by using the color space analysis model to obtain the analysis result. That is, the parsing and evaluation module 131 parses the information header of the self-check area data and evaluates the validity of the self-check area data; the calculation module 132 calculates the self-check area data, that is, counts the data area length features, pixel data magnitude features, data arrangement features, etc. between two consecutive frames of data in the self-check area to obtain the data area features; the analysis module 133 estimates and analyzes the color space where the current data area features are located by using the color space analysis model to obtain the analysis result.

[0063] In this embodiment, the difference analysis module 14 includes: a color difference analysis and statistics module 141 for performing color difference analysis and statistics on the analysis result to obtain color difference information; a brightness difference analysis and statistics module 142 for performing brightness difference analysis and statistics on the analysis result to obtain brightness difference information; a shape difference analysis and statistics module 143 for performing shape difference analysis and statistics on the analysis result to obtain shape difference information; an edge difference analysis and statistics module 144 for performing edge difference analysis and statistics on the analysis result to obtain edge difference information; and a difference information determination module 145 for determining the difference information based on the color difference information, the brightness difference information, the shape difference information, and the edge difference information. That is, the difference analysis module 14 analyzes and statistics the color, brightness, shape, and edge differences between the analysis result of the current data and the analysis result of the previous frame data, and finally determines the difference information based on the color difference information, the brightness difference information, the shape difference information, and the edge difference information.

[0064] In this embodiment, the self-check module 15 includes: a color difference self-check module 151 for performing abnormal calculation on the color difference analysis and statistics module according to the abnormal type to complete the color difference self-check; a brightness difference self-check module 152 for performing abnormal calculation on the brightness difference analysis and statistics module according to the abnormal type to complete the brightness difference self-check; a shape difference self-check module 153 for performing abnormal calculation on the shape difference analysis and statistics module according to the abnormal type to complete the shape difference self-check; and an edge difference self-check module 154 for performing abnormal calculation on the edge difference analysis and statistics module according to the abnormal type to complete the edge difference self-check. That is, the self-check module 15 performs abnormal calculation on the difference information in the difference analysis module 14, updates the difference evaluation result, and thus infers the abnormal type to complete the self-check.

[0065] In addition, the image signal processing self-check system further includes: a queue detection module 18 for detecting whether there is still unprocessed self-check area data in the self-check data area of the self-check area data management module; and a jump module 19 for, if there is still unprocessed self-check area data in the self-check data area, jumping to the step of parsing and calculating the unprocessed self-check area data by using the color space unification module until there is no unprocessed self-check area data in the self-check data area.

[0066] The present application proposes an image signal processing self-check system, which mainly includes: an algorithm data area mapping module 11, a self-check area data management module 12, a color space unification module 13, a difference analysis module 14, and a self-check module 15. Among them, the algorithm data area mapping module 11 mainly binds the output data area memory of each algorithm module and the self-check data area memory; the self-check area data management module 12 is mainly responsible for enqueueing, dequeueing, and memory management of image data; since the color spaces of image algorithm modules may be different, the color space unification module 13 is introduced, which mainly analyzes the color space where the current data area is located based on the difference in the characteristics of the self-check area data; the difference analysis module 14 mainly performs a difference statistical analysis on the color, brightness, shape, and edges of the analysis results corresponding to the self-check area data; the self-check module 15 mainly determines the type of abnormality according to the difference information, performs an abnormality calculation on the difference analysis module 14 according to the type of abnormality, and completes the self-check process. Thus, the preliminary evaluation and detection of each algorithm module are automatically completed, and for hardware and software developers, the abnormal algorithm module can be efficiently located, and for algorithm debugging personnel, the parameter abnormalities of each level of algorithm module can be quickly discovered.

[0067] In this embodiment, the algorithm data area mapping module is used to establish a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module; the self-check area data management module is used to cache the output area data in the output data area memory to the self-check data area memory based on the mapping relationship, and determine whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, the self-check area data is output; the color space unification module is used to parse and calculate the self-check area data to obtain data area characteristics, and analyze the data area characteristics by using a preset color space analysis model to obtain an analysis result; the difference analysis module is used to perform a difference analysis on the analysis result to obtain difference information; the self-check module is used to determine the type of abnormality based on the difference information, and perform an abnormality calculation on the difference analysis module according to the type of abnormality to complete the self-check. The present application caches the output area data to the self-check data area memory by using the mapping relationship between the output data area memory of each module and the self-check data area memory in the self-check area data management module. If the self-check data area memory reaches the preset threshold, the self-check area data is parsed and calculated to obtain data area characteristics, and the data area characteristics are analyzed and the difference analysis is performed by using the color space analysis model to obtain the difference type, thereby obtaining the type of abnormality, performing an abnormality inference, and completing the self-check. The present application can automatically implement the evaluation and self-check of each module in the image signal processing self-check system, simplify the image signal processing self-check and module debugging process, and can efficiently and quickly locate the abnormal algorithm module, improving the efficiency of image signal processing self-check.

[0068] SeeFigure 2 As shown in Figure 2 , an embodiment of the present invention discloses an image signal processing self-checking method, including:

[0069] Step S21: Establish a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module through the algorithm data area mapping module.

[0070] Step S22: Cache the output area data in the output data area memory to the self-check data area memory through the self-check area data management module and based on the mapping relationship, and determine whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, output the self-check area data.

[0071] Step S23: Parse and calculate the self-check area data through the color space unification module to obtain data area features, and analyze the data area features using a preset color space analysis model to obtain an analysis result.

[0072] Step S24: Perform differential analysis on the analysis result through the differential analysis module to obtain differential information.

[0073] Step S25: Determine the abnormal type through the self-check module and based on the differential information, and perform abnormal calculation on the differential analysis module according to the abnormal type to complete the self-check.

[0074] The specific process of this application is as Figure 3As shown in the figure, (1) establish the mapping relationship between the output data area memory and the self-check data area memory of each module through the algorithm data area mapping module; (2) load the scene configuration parameters and image sensor configuration parameters through the parameter loading module; (3) initialize the pipeline state machine through the initialization and execution module; (4) cache the output area data in the output data area memory to the self-check data area memory through the self-check area data management module and based on the mapping relationship; (5) determine whether the self-check data area memory reaches the preset threshold. If the self-check data area memory reaches the preset threshold, output the self-check area data; (6) perform operations on the self-check area data information header through the color space unification module to obtain the parsing result and evaluate the data validity of the parsing result; (7) calculate the data area features; (8) analyze the data area features using the color space analysis model to obtain the analysis result; (9) perform color, brightness, shape, and edge difference analysis and statistics on the analysis result through the difference analysis module to obtain the difference information; (10) detect whether there is still unprocessed self-check area data in the self-check data area of the self-check area data management module (that is, determine whether the data area queue in the self-check data area is empty); (11) if it is empty, determine the abnormal type based on the difference information, and perform abnormal calculation on the difference analysis module according to the abnormal type to complete the self-check; if it is not empty, jump to the step of parsing and calculating the unprocessed self-check area data using the color space unification module until there is no unprocessed self-check area data in the self-check data area.

[0075] In this embodiment, a mapping relationship is established between the output data area memory of each local module and the self-check data area memory in the self-check area data management module through the algorithm data area mapping module; the output area data in the output data area memory is cached to the self-check data area memory through the self-check area data management module and based on the mapping relationship, and it is judged whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, the self-check area data is output; the self-check area data is parsed and calculated by the color space unification module to obtain data area features, and the data area features are analyzed by using a preset color space analysis model to obtain an analysis result; the analysis result is analyzed for differences by the difference analysis module to obtain difference information; the abnormal type is determined by the self-check module and based on the difference information, and the difference analysis module is abnormally deduced according to the abnormal type to complete the self-check. In this application, the output area data is cached to the self-check data area memory by using the mapping relationship between the output data area memory of each module and the self-check data area memory in the self-check area data management module. If the self-check data area memory reaches the preset threshold, the self-check area data is parsed and calculated to obtain data area features, and the data area features are analyzed and differentially analyzed by using the color space analysis model to obtain a difference type, so as to obtain an abnormal type and perform abnormal inference to complete the self-check. This application can automatically implement the evaluation and self-check of each module in the image signal processing self-check system, simplify the image signal processing self-check and module debugging process, and can efficiently and quickly locate the abnormal algorithm module, improving the efficiency of the image signal processing self-check.

[0076] Figure 4 FIG. is a schematic structural diagram of an image signal processing self-check device provided by an embodiment of the present application. The image signal processing self-check device 20 may specifically include: at least one processor 21, at least one memory 22, a power supply 23, a communication interface 24, an input / output interface 25, and a communication bus 26. Among them, the memory 22 is used to store a computer program, and the computer program is loaded and executed by the processor 21 to implement the relevant steps in the image signal processing self-check method executed by the electronic device disclosed in any of the foregoing embodiments.

[0077] In this embodiment, the power supply 23 is used to provide working voltage for each hardware device on the image signal processing self-check device 20; the communication interface 24 can create a data transmission channel between the image signal processing self-check device 20 and external devices, and the communication protocol it follows is any communication protocol applicable to the technical solution of the present application, and no specific limitation is imposed on it here; the input / output interface 25 is used to obtain external input data or output data to the outside, and its specific interface type can be selected according to specific application needs, and no specific limitation is made here.

[0078] In addition, as a carrier for storing resources, the memory 22 can be a read-only memory, a random access memory, a magnetic disk, an optical disk, etc. The resources stored thereon include an operating system 221, a computer program 222, data 223, etc. The storage method can be temporary storage or permanent storage.

[0079] Among them, the operating system 221 is used to manage and control each hardware device on the image signal processing self-checking device 20 and the computer program 222, so as to enable the processor 21 to perform operations and processing on the data 223 in the memory 22. It can be Windows, Unix, Linux, etc. In addition to the computer program that can be used to complete the image signal processing self-checking method executed by the image signal processing self-checking device 20 disclosed in any of the foregoing embodiments, the computer program 222 can further include computer programs that can be used to complete other specific tasks. In addition to the data transmitted by external devices received by the image signal processing self-checking device, the data 223 can also include data collected by its own input / output interface 25, etc.

[0080] The steps of the methods or algorithms described in connection with the embodiments disclosed herein can be implemented directly in hardware, software modules executed by a processor, or a combination of both. The software module can be placed in a random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0081] Furthermore, an embodiment of the present application also discloses a computer-readable storage medium. When the computer program stored in the storage medium is loaded and executed by a processor, the steps of the image signal processing self-checking method disclosed in any of the foregoing embodiments are implemented.

[0082] Finally, it should also be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0083] The above has introduced in detail an image signal processing self-check system, method, device and storage medium provided by the present invention. Specific examples are used in this article to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. An image signal processing self-check system, characterized in that, It includes: An algorithm data area mapping module, which is used to establish a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module; A self-check area data management module, which is used to cache the output area data in the output data area memory to the self-check data area memory based on the mapping relationship, and determine whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, self-check area data is output; A color space unification module, which is used to parse and calculate the self-check area data to obtain data area features, and analyze the data area features by using a preset color space analysis model to obtain an analysis result; A difference analysis module, which is used to perform difference analysis on the analysis result to obtain difference information; A self-check module, which is used to determine the abnormal type based on the difference information, and perform abnormal calculation on the difference analysis module according to the abnormal type to complete the self-check.

2. The image signal processing self-checking system according to claim 1, characterized in that It also includes: A parameter loading module, which is used to load the scene configuration parameters and image sensor configuration parameters of image signal processing; An initialization and execution module, which is used to perform an initialization operation on the pipeline state machine to obtain the initialized pipeline state machine, and execute the initialized pipeline state machine.

3. The image signal processing self-checking system according to claim 2, wherein, The self-check area data management module includes: A data enqueue cache module, which is used to obtain the Mobile Industry Processor Interface data sent by the initialized pipeline state machine, and obtain the output area data in the output data area memory, and cache the Mobile Industry Processor Interface data and the output area data to the local self-check data area memory based on the mapping relationship; A judgment module, which is used to judge whether the self-check data area memory reaches the preset threshold; A data dequeue module, which is used to output self-check area data if the self-check data area memory reaches the preset threshold.

4. The image signal processing self-checking system according to claim 1, wherein The color space unification module includes: A parsing and evaluation module, which is used to parse the information header of the self-check area data to obtain a parsing result, and evaluate the data validity of the parsing result; A calculation module, which is used to calculate the self-check area data to obtain the data area features if the data validity evaluation passes; An analysis module, which is used to analyze the data area features by using the color space analysis model to obtain the analysis result.

5. The image signal processing self-check system according to claim 1, characterized in that, The difference analysis module includes: A color difference analysis and statistics module, which is used to perform color difference analysis and statistics on the analysis result to obtain color difference information; A brightness difference analysis and statistics module, which is used to perform brightness difference analysis and statistics on the analysis result to obtain brightness difference information; A shape difference analysis and statistics module, which is used to perform shape difference analysis and statistics on the analysis result to obtain shape difference information; An edge difference analysis and statistics module, which is used to perform edge difference analysis and statistics on the analysis result to obtain edge difference information; A difference information determination module, which is used to determine the difference information based on the color difference information, the brightness difference information, the shape difference information, and the edge difference information.

6. The image signal processing self-check system according to claim 5, wherein The self-check module includes: A color difference self-check module, configured to perform abnormal calculation on the color difference analysis and statistics module according to the abnormal type, so as to complete color difference self-check; A brightness difference self-check module, configured to perform abnormal calculation on the brightness difference analysis and statistics module according to the abnormal type, so as to complete brightness difference self-check; A shape difference self-check module, configured to perform abnormal calculation on the shape difference analysis and statistics module according to the abnormal type, so as to complete shape difference self-check; An edge difference self-check module, configured to perform abnormal calculation on the edge difference analysis and statistics module according to the abnormal type, so as to complete edge difference self-check.

7. The image signal processing self-check system according to any one of claims 1 to 6, characterized in that It further includes: A queue detection module, configured to detect whether there is still unprocessed self-check area data in the self-check data area of the self-check area data management module; A jump module, configured to, if there is still unprocessed self-check area data in the self-check data area, jump to the step of parsing and calculating the unprocessed self-check area data by using the color space unification module until there is no such unprocessed self-check area data in the self-check data area.

8. An image signal processing self-check method, characterized in that, It includes: Establish a mapping relationship between the output data area memory of each local module and the self-check data area memory in the self-check area data management module through the algorithm data area mapping module; Cache the output area data in the output data area memory to the self-check data area memory through the self-check area data management module and based on the mapping relationship, and determine whether the self-check data area memory reaches a preset threshold. If the self-check data area memory reaches the preset threshold, output the self-check area data; Parse and calculate the self-check area data through the color space unification module to obtain data area features, and analyze the data area features by using a preset color space analysis model to obtain an analysis result; Perform difference analysis on the analysis result through the difference analysis module to obtain difference information; Determine the abnormal type through the self-check module and based on the difference information, and perform abnormal calculation on the difference analysis module according to the abnormal type to complete self-check.

9. An electronic device, characterized in that, It includes: A memory, configured to store a computer program; A processor, configured to execute the computer program to implement the image signal processing self-check method as claimed in claim 8.

10. A computer-readable storage medium, characterized in that, For storing a computer program; wherein, when the computer program is executed by the processor, it implements the image signal processing self-check method as claimed in claim 8.

Images