A driving video processing method, device and equipment and storage medium

Abstract

This invention discloses a method, apparatus, device, and storage medium for processing driving images. The method includes the following steps: in response to the startup of the vehicle's infotainment system, if it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance anomaly processing strategy is implemented to obtain a target white balance coefficient; based on the target white balance coefficient, the texture value of the current frame image is calculated; based on the verification result of the texture value, it is determined whether the texture value needs to be corrected; if it is determined that the texture value needs to be corrected, image rendering is performed based on the corrected texture value, and the rendered image is output to the vehicle display device. This application significantly improves the color accuracy and stability of the camera output image, effectively avoids the problem of subsequent texture value calculation errors caused by initial white balance coefficient anomalies, and allows for rapid fault location and troubleshooting when problems occur, reducing maintenance costs and improving system maintainability.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method, apparatus, device, and storage medium for processing driving images. Background Technology

[0002] With the rapid development of intelligent connected vehicle technology, surround-view cameras (AVMs) have become standard equipment in vehicle infotainment systems. They collect images from multiple perspectives around the vehicle, and after image processing such as stitching and rendering, ultimately present a 360-degree panoramic view on the vehicle's display screen, providing driving and parking assistance to the driver. In this process, the accurate calculation and stable output of image texture values ​​directly determine the color fidelity and visual coherence of the panoramic image.

[0003] In the current image output process of in-vehicle infotainment systems and other devices, there are several issues affecting image quality and system stability. For example, in white balance coefficient processing, if the white balance coefficient obtained from the camera upon initial power-on is 0, subsequent calculated white balance coefficient values ​​will always be 0. This can lead to image color deviation or the inability to properly display texture values. Furthermore, the current process lacks an effective verification mechanism for texture value calculation and processing, making it difficult to guarantee the accuracy and stability of image output and hindering troubleshooting when problems occur.

[0004] Therefore, ensuring the accuracy and stability of image output to facilitate troubleshooting when problems occur is a pressing technical issue that needs to be addressed. Summary of the Invention

[0005] The main objective of this invention is to provide a driving image processing method, apparatus, device, and storage medium that significantly improves the color accuracy and stability of camera output images, effectively avoids the problem of subsequent texture value calculation errors caused by abnormal initial white balance coefficients, and allows for rapid fault location and troubleshooting when problems occur, reducing maintenance costs and improving system maintainability.

[0006] In a first aspect, this application provides a method for processing driving images, wherein the method includes the following steps: In response to the startup of the vehicle system, if it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance anomaly processing strategy is implemented to obtain the target white balance coefficient. Calculate the texture value of the current frame image based on the target white balance coefficient; Based on the verification results of the texture value, determine whether the texture value needs to be corrected; If it is determined that the texture value needs to be corrected, then image rendering is performed based on the corrected texture value, and the rendered image is output to the vehicle display device.

[0007] In conjunction with the first aspect mentioned above, as an optional implementation method, the current white balance coefficient of the camera is obtained; If the white balance coefficient is determined to be 0, then the white balance coefficient is obtained again; If the result of repeatedly re-acquiring the white balance coefficient is still 0, then the default value will be used as the target white balance coefficient. If the white balance coefficient is determined to be non-zero or the white balance coefficient obtained continuously is non-zero, then the currently obtained white balance coefficient is taken as the target white balance coefficient.

[0008] In conjunction with the first aspect mentioned above, as an optional implementation, a recursive calculation method is adopted. Based on the texture value of the previous frame image and the target white balance coefficient, the texture value of the current frame image is calculated, wherein, according to the formula: Calculate the texture value of the current frame image, where To obtain the camera's white balance coefficient, This is the texture value of the previous frame, where if the current frame is the first frame, then... The default values ​​are set as the lower and upper limits, which represent the minimum and maximum values ​​corresponding to the set texture value range, respectively.

[0009] In conjunction with the first aspect mentioned above, as an optional implementation method, the reasonableness of the texture value calculated for each frame is checked; it is determined whether the texture value is within a preset texture value range. If the texture value of the current frame exceeds the texture value range, then it is determined that the texture value of the current frame should be corrected, and the corrected texture value is used to obtain the target texture value. If the texture value of the current frame is within the texture value range, then it is determined that no correction is needed, and the texture value of the current frame is used as the target texture value.

[0010] In conjunction with the first aspect mentioned above, as an optional implementation, if the texture value of the current frame is greater than the maximum value in the texture value range... Then the scaling ratio The maximum value ; If the texture value of the current frame is less than the minimum value of the texture value range Then the scaling ratio The minimum value ; According to the formula: Texture values ​​that exceed the preset texture value range are corrected to ensure that the texture value of the current frame falls within the preset texture value range. This is the texture value for the current frame.

[0011] In conjunction with the first aspect mentioned above, as an optional implementation method, the corrected texture value is fed back for the calculation of the texture value of the next frame, and the texture value of the next frame is used to render the camera image, so as to render the image to the vehicle display device to display the driving image.

[0012] In conjunction with the first aspect mentioned above, as an optional implementation, the camera is initialized, the camera parameters are configured, and the graphics processor resources and graphics library rendering commands are initialized.

[0013] Secondly, this application provides a vehicle image processing device, the device comprising: The processing module is used to respond to the start of the vehicle system. If it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance abnormality processing strategy is implemented to obtain the target white balance coefficient. A calculation module is used to calculate the texture value of the current frame image based on the target white balance coefficient; The correction module is used to determine whether the texture value needs to be corrected based on the verification result of the texture value; The rendering module is used to render an image based on the corrected texture value if it is determined that the texture value needs to be corrected, and to output the rendered image to the vehicle display device.

[0014] Thirdly, this application also provides an electronic device, the electronic device comprising: a processor; and a memory storing computer-readable instructions, which, when executed by the processor, implement the method described in any one of the first aspects.

[0015] Fourthly, this application also provides a computer-readable storage medium storing computer program instructions that, when executed by a computer, cause the computer to perform the method described in any of the first aspects.

[0016] This application provides a driving image processing method, apparatus, device, and storage medium. The method includes the following steps: in response to the startup of the vehicle's infotainment system, if it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance anomaly processing strategy is implemented to obtain a target white balance coefficient; based on the target white balance coefficient, the texture value of the current frame image is calculated; based on the verification result of the texture value, it is determined whether the texture value needs to be corrected; if it is determined that the texture value needs to be corrected, image rendering is performed based on the corrected texture value, and the rendered image is output to the vehicle display device. This application significantly improves the color accuracy and stability of the camera output image, effectively avoids the problem of subsequent texture value calculation errors caused by initial white balance coefficient anomalies, and quickly locates and troubleshoots faults when problems occur, reducing maintenance costs and improving system maintainability.

[0017] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit the invention. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0019] Figure 1 This is a flowchart of a vehicle image processing method provided in the embodiments of this application; Figure 2 This is a schematic diagram of a vehicle image processing device provided in the embodiments of this application; Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of this application; Figure 4 This is a schematic diagram of a computer-readable program medium provided in an embodiment of this application. Detailed Implementation

[0020] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the invention as detailed in the appended claims.

[0021] Furthermore, the accompanying drawings are merely illustrative of this disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the drawings represent functional entities and do not necessarily correspond to physically or logically independent entities.

[0022] The embodiments of this application will be further described in detail below with reference to the accompanying drawings.

[0023] Reference Figure 1 , Figure 1 The diagram shown is a flowchart of a vehicle image processing method provided by the present invention. Figure 1 As shown, the method includes the following steps: Step S101: In response to the start of the vehicle system, if it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance abnormality processing strategy is implemented to obtain the target white balance coefficient.

[0024] Specifically, in response to the vehicle's infotainment system starting up, the camera is initialized, its parameters are configured, and the graphics processor resources and graphics library rendering commands are initialized. For example, after the vehicle's infotainment system starts up, the camera is initialized, configuring the resolution parameters to 30 frames per second and 1920×1080; OpenGL shader commands are loaded; GPU resources are initialized, and video memory is allocated to ensure that the GPU can process image data normally.

[0025] Then, the current white balance coefficient of the camera is obtained. If the white balance coefficient is determined to be 0, the white balance coefficient is obtained again. If the result of obtaining the white balance coefficient multiple times is still 0, the default value is used as the target white balance coefficient. If the white balance coefficient is determined to be not 0 or the white balance coefficient obtained repeatedly is not 0, the currently obtained white balance coefficient is used as the target white balance coefficient.

[0026] To illustrate this with an example, during the first frame of a vehicle's cold start, the system initially obtains a white balance coefficient N=0, triggering a retry mechanism. If the result of three consecutive re-obtaining values ​​is 0, it is considered abnormal, and the default value of 128 is used as the target white balance coefficient. In the second frame, N=0 is obtained for the first time, and N=150 (non-zero) is obtained during the first retry. Retrying stops, and 150 is used as the target white balance coefficient. In the third frame, N=148 (non-zero) is obtained for the first time, and 148 is directly used as the target white balance coefficient without retrying.

[0027] This means obtaining the white balance coefficient N (0–255, 128 is neutral) from the camera. If N=0 and the result is still 0 after retries (e.g., 3 times), then the default value of 128 is used as the valid N; if N≠0, then the value is used directly.

[0028] Step S102: Calculate the texture value of the current frame image based on the target white balance coefficient.

[0029] Specifically, a recursive calculation method is used to calculate the texture value of the current frame image based on the texture value of the previous frame image and the target white balance coefficient, wherein, according to the formula: Calculate the texture value of the current frame image, where To obtain the camera's white balance coefficient, This is the texture value of the previous frame, where if the current frame is the first frame, then... The default values ​​are set as the lower and upper limits, which represent the minimum and maximum values ​​corresponding to the set texture value range, respectively.

[0030] To illustrate this more clearly, let's take an example: when the car's infotainment system is first turned on, there is no... The first frame uses the default value (128), and the texture value of the second frame depends on the texture value calculated in the first frame. ,in, The white balance coefficient of the camera is obtained. If it is 0, the obtained white balance coefficient is set to the default value (128). The upper and lower limits mean that the calculated texture values ​​must be within (lower limit Lmin, upper limit Lmax). This is understandable. That is, the white balance gain used for texture rendering in the current frame (or the texture value generated from it), and updated. = .

[0031] Step S103: Based on the verification result of the texture value, determine whether the texture value needs to be corrected.

[0032] Specifically, the reasonableness of the texture value calculated for each frame is checked; it is determined whether the texture value is within the preset texture value range. If the texture value of the current frame exceeds the texture value range, then it is determined that the texture value of the current frame should be corrected, and the corrected texture value is used to obtain the target texture value. If the texture value of the current frame is within the texture value range, then it is determined that no correction is needed, and the texture value of the current frame is used as the target texture value.

[0033] Wherein, if the texture value of the current frame is greater than the maximum value of the texture value range. Then the scaling ratio The maximum value ; If the texture value of the current frame is less than the minimum value of the texture value range Then the scaling ratio The minimum value ; According to the formula: Texture values ​​that exceed the preset texture value range are corrected to ensure that the texture value of the current frame falls within the preset texture value range. This is the texture value for the current frame.

[0034] To illustrate this more clearly, the texture value calculated for each frame is validated for reasonableness to determine if it falls within a preset reasonable range. If it exceeds the range, it is corrected (e.g., replaced with a valid value from the previous frame or a default value), and the error is recorded. The same validation is performed on the first frame to ensure the initial value is valid.

[0035] Correction method: Linear scaling For each frame, the texture value V is checked to see if it falls within a preset reasonable range. If it exceeds the range, linear scaling correction is used. The calculation formula is to check whether the texture value V obtained for each frame is within the preset reasonable range. )Inside.

[0036] If the value exceeds the range, a linear scaling correction is applied, calculated using the following formula: like Then the scaling ratio ; like Then the scaling ratio ; otherwise Corrected texture values This will bring it within a reasonable range.

[0037] In one embodiment, for example, if the reasonable range is [10, 200], the calculated texture value is 220, the scaling factor k = 200 / 220 ≈ 0.909, and the corrected texture value... =220×0.909≈200.

[0038] Step S104: If it is determined that the texture value needs to be corrected, then the image is rendered based on the corrected texture value, and the rendered image is output to the vehicle display device.

[0039] Specifically, the corrected texture value is fed back to calculate the texture value of the next frame, and the texture value of the next frame is used to render the camera image, so as to render the image to the in-vehicle display device to display the driving image.

[0040] Understandably, the processed and verified camera image texture is fed back for texture calculation in the next frame. Simultaneously, this texture value is used to render the camera image, which is then rendered onto the display device using graphics libraries such as OpenGL, ultimately becoming part of the driving video feed for the user to view.

[0041] In one embodiment, the log records the specific values ​​of relevant parameters (such as the obtained N value and the calculated texture value) and status information such as whether the operation was successful during the execution of steps such as obtaining the white balance coefficient N, calculating the texture value, providing feedback on the texture value, and rendering the image. The recorded logs are stored locally on the device or uploaded to a server for review and analysis in case of problems.

[0042] In summary, when the camera is activated, if the white balance coefficient (a parameter used to adjust image color) is detected to be 0 (indicating invalidity), the system will attempt to reacquire the correct value multiple times; if it still cannot be obtained, the default value of 128 will be used instead. Next, the system will check whether the texture value in image processing is within a reasonable range (e.g., 10 to 200); if it exceeds the range, it will be automatically corrected. Simultaneously, the system will record the details of each operation step (such as the acquired coefficient values ​​and calculation results). This way, if image problems occur, maintenance personnel can directly review the records to quickly identify the cause and avoid image color distortion or display abnormalities.

[0043] The beneficial effects of this application include: 1. By optimizing the white balance coefficient processing mechanism, the problem of subsequent texture value calculation errors caused by the initial white balance coefficient being 0 is avoided, thereby improving the color accuracy of the image.

[0044] 2. The added texture value verification step ensures the rationality of the output texture value and improves the stability and reliability of image output.

[0045] 3. The logging function for key steps facilitates quick location and troubleshooting when problems occur, reducing maintenance costs and improving system maintainability.

[0046] Reference Figure 2 , Figure 2 The diagram shown is a schematic of a vehicle image processing device provided by the present invention. Figure 2 As shown, the device includes: The processing module 201 is used to respond to the start of the vehicle system. If it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance abnormality processing strategy is implemented to obtain the target white balance coefficient. The calculation module 202 is used to calculate the texture value of the current frame image based on the target white balance coefficient; The correction module 203 is used to determine whether the texture value needs to be corrected based on the verification result of the texture value; The rendering module 204 is used to render an image based on the corrected texture value if it is determined that the texture value needs to be corrected, and output the rendered image to the vehicle display device.

[0047] Furthermore, in one possible implementation, the processing module is also used to obtain the current white balance coefficient of the camera; If the white balance coefficient is determined to be 0, then the white balance coefficient is obtained again; If the result of repeatedly re-acquiring the white balance coefficient is still 0, then the default value will be used as the target white balance coefficient. If the white balance coefficient is determined to be non-zero or the white balance coefficient obtained continuously is non-zero, then the currently obtained white balance coefficient is taken as the target white balance coefficient.

[0048] Furthermore, in one possible implementation, the calculation module is also used to calculate the texture value of the current frame image using a recursive calculation method, based on the texture value of the previous frame image and the target white balance coefficient, wherein, according to the formula: Calculate the texture value of the current frame image, where To obtain the camera's white balance coefficient, This is the texture value of the previous frame, where if the current frame is the first frame, then... The default values ​​are set as the lower and upper limits, which represent the minimum and maximum values ​​corresponding to the set texture value range, respectively.

[0049] Furthermore, in one possible implementation, the correction module is also used to perform a reasonableness check on the texture value calculated for each frame; and to determine whether the texture value is within a preset texture value range; If the texture value of the current frame exceeds the texture value range, then it is determined that the texture value of the current frame should be corrected, and the corrected texture value is used to obtain the target texture value. If the texture value of the current frame is within the texture value range, then it is determined that no correction is needed, and the texture value of the current frame is used as the target texture value.

[0050] Furthermore, in one possible implementation, the correction module is also configured to, if the texture value of the current frame is greater than the maximum value of the texture value range... Then the scaling ratio The maximum value ; If the texture value of the current frame is less than the minimum value of the texture value range Then the scaling ratio The minimum value ; According to the formula: Texture values ​​that exceed the preset texture value range are corrected to ensure that the texture value of the current frame falls within the preset texture value range. This is the texture value for the current frame.

[0051] Furthermore, in one possible implementation, the rendering module is also used to feed back the corrected texture value for the texture value calculation of the next frame, and use the texture value of the next frame to render the camera image, so as to render the image to the vehicle display device to display the driving image.

[0052] Furthermore, in one possible implementation, the processing module is also used to initialize the camera, configure the camera parameters, and initialize the graphics processor resources and graphics library rendering commands.

[0053] The following reference Figure 3 To describe an electronic device 300 according to this embodiment of the present invention. Figure 3 The electronic device 300 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0054] like Figure 3 As shown, the electronic device 300 is presented in the form of a general-purpose computing device. The components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, and a bus 330 connecting different system components (including storage unit 320 and processing unit 310).

[0055] The storage unit stores program code that can be executed by the processing unit 310, causing the processing unit 310 to perform the steps described in the "Embodiment Methods" section of this specification according to various exemplary embodiments of the present invention.

[0056] Storage unit 320 may include readable media in the form of volatile storage units, such as random access memory (RAM) 321 and / or cache memory 322, and may further include read-only memory (ROM) 323.

[0057] Storage unit 320 may also include a program / utility 324 having a set (at least one) of program modules 325, including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0058] Bus 330 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0059] Electronic device 300 can also communicate with one or more external devices (e.g., keyboard, pointing device, Bluetooth device, etc.), one or more devices that enable a user to interact with electronic device 300, and / or any device that enables electronic device 300 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 350. Furthermore, electronic device 300 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 360. As shown, network adapter 360 communicates with other modules of electronic device 300 via bus 330. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0060] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0061] According to the present disclosure, a computer-readable storage medium is also provided, on which a program product capable of implementing the methods described above is stored. In some possible embodiments, various aspects of the present invention can also be implemented as a program product comprising program code that, when the program product is run on a terminal device, causes the terminal device to perform the steps of the various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0062] refer to Figure 4 As shown, a program product 400 for implementing the above-described method according to an embodiment of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0063] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, 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.

[0064] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0065] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0066] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0067] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0068] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

[0069] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

Claims

1. A method for processing driving images, characterized in that, include: In response to the startup of the vehicle system, if it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance anomaly processing strategy is implemented to obtain the target white balance coefficient. Calculate the texture value of the current frame image based on the target white balance coefficient; Based on the verification results of the texture value, determine whether the texture value needs to be corrected; If it is determined that the texture value needs to be corrected, then image rendering is performed based on the corrected texture value, and the rendered image is output to the vehicle display device.

2. The method according to claim 1, characterized in that, If the obtained white balance coefficient of the camera is determined to be an outlier, a white balance anomaly processing strategy is implemented to obtain the target white balance coefficient, including: Obtain the current white balance coefficient of the camera; If the white balance coefficient is determined to be 0, then the white balance coefficient is obtained again; If the result of repeatedly re-acquiring the white balance coefficient is still 0, then the default value will be used as the target white balance coefficient. If the white balance coefficient is determined to be non-zero or the white balance coefficient obtained continuously is non-zero, then the currently obtained white balance coefficient is taken as the target white balance coefficient.

3. The method according to claim 1, characterized in that, The step of calculating the texture value of the current frame image based on the target white balance coefficient includes: Using a recursive calculation method, the texture value of the current frame image is calculated based on the texture value of the previous frame image and the target white balance coefficient, wherein, according to the formula: Calculate the texture value of the current frame image, where To obtain the camera's white balance coefficient, This is the texture value of the previous frame, where if the current frame is the first frame, then... The default values ​​are set as the lower and upper limits, which represent the minimum and maximum values ​​corresponding to the set texture value range, respectively.

4. The method according to claim 1, characterized in that, The step of determining whether the texture value needs to be corrected based on the verification result of the texture value includes: Perform a reasonableness check on the texture value calculated for each frame; determine whether the texture value is within the preset texture value range; If the texture value of the current frame exceeds the texture value range, then it is determined that the texture value of the current frame should be corrected, and the corrected texture value is used to obtain the target texture value. If the texture value of the current frame is within the texture value range, then it is determined that no correction is needed, and the texture value of the current frame is used as the target texture value.

5. The method according to claim 4, characterized in that, include: If the texture value of the current frame is greater than the maximum value in the texture value range Then the scaling ratio The maximum value ; If the texture value of the current frame is less than the minimum value of the texture value range Then the scaling ratio The minimum value ; According to the formula: Texture values ​​that exceed the preset texture value range are corrected to ensure that the texture value of the current frame falls within the preset texture value range. This is the texture value for the current frame.

6. The method according to claim 1, characterized in that, The step of rendering the image based on the corrected texture values ​​and outputting the rendered image to the vehicle display device includes: The corrected texture value is fed back to calculate the texture value of the next frame, and the texture value of the next frame is used to render the camera image, so as to render the image to the vehicle display device to display the driving image.

7. The method according to claim 1, characterized in that, The response after the vehicle's infotainment system is started includes: The camera is initialized, its parameters are configured, and the graphics processor resources and graphics library rendering commands are initialized.

8. A vehicle image processing device, characterized in that, include: The processing module is used to respond to the start of the vehicle system. If it is determined that the current white balance coefficient of the acquired camera is an abnormal value, a white balance abnormality processing strategy is implemented to obtain the target white balance coefficient. A calculation module is used to calculate the texture value of the current frame image based on the target white balance coefficient; The correction module is used to determine whether the texture value needs to be corrected based on the verification result of the texture value; The rendering module is used to render an image based on the corrected texture value if it is determined that the texture value needs to be corrected, and to output the rendered image to the vehicle display device.

9. An electronic device, characterized in that, The electronic device includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer program instructions that, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 7.

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