WO2021143281A1

WO2021143281A1 - Color shading correction method, terminal device, and computer-readable storage medium

Info

Publication number: WO2021143281A1
Application number: PCT/CN2020/125379
Authority: WO
Inventors: 胡宏伟; 姚添宇; 卢曰万; 赵琳; 郜文美
Original assignee: 华为技术有限公司
Priority date: 2020-01-13
Filing date: 2020-10-30
Publication date: 2021-07-22
Also published as: CN113129222A

Abstract

Provided are a color shading correction method, a terminal device and a computer-readable storage medium, which are applicable to the technical field of image processing. The method comprises: acquiring an image to be corrected (S401); and on the basis of pre-calibrated color shading data, carrying out color shading correction on the image to be corrected, wherein the color shading data comprises color shading data of at least two types of monochromatic light (S402). In the method, by means of carrying out color shading correction on an image by using color shading data of a plurality of types of monochromatic light, color shading forms in various color temperature scenarios can be effectively covered, and the accuracy of color shading correction is improved. In the process of carrying out color shading correction by using color shading data of a plurality of types of monochromatic light, color shading estimation can be carried out by using pixel positions of pixel points corresponding to a main color of an image to be corrected, so as to further improve the accuracy of color shading correction; and color shading correction can be carried out by using a small number of bases extracted from the color shading data, so as to reduce the requirements of an algorithm for storage space.

Description

Color shading correction method, terminal equipment and computer readable storage medium

This application claims the priority of a Chinese patent application filed with the State Intellectual Property Office, the application number is 202010030184.1, and the application name is "color shading correction method, terminal equipment and computer-readable storage medium" on January 13, 2020, and its entire content Incorporated in this application by reference.

Technical field

This application belongs to the field of image processing technology, and in particular relates to a color shading correction method, terminal equipment, chip, and computer-readable storage medium.

Background technique

With the continuous development of science and technology such as Artificial Intelligence (AI), terminal equipment, and image processing, the design of mobile phones and other terminal equipment is becoming lighter and lighter, and the volume of integrated camera modules is becoming smaller and smaller, resulting in The problem of inconsistent colors between the center and the edges of the scene of the same color in the image captured by the terminal device through the camera module is called color shading.

Color shading is part of lens shading. The reason for the color shading is that the camera module usually installs an infrared cut filter (IR-Cut Filter) before the image sensor in order to block the influence of infrared light on the image sensor. The light transmittance of the infrared cut filter changes with the angle of incidence, resulting in high red light transmittance in the center area of the infrared cut filter and low red light transmittance in the edge area, which leads to the appearance of images taken by the terminal device The phenomenon of reddish center. In order to improve the image effect taken by the terminal device, it is generally necessary to perform color shading correction on the taken pictures.

Currently, shading correction parameters are generally used to perform color shading correction on an image. By pre-saving the light source color temperature information of the image and the shadow correction coefficient corresponding to the color temperature, the shadow correction coefficient corresponding to the color temperature is found based on the color temperature in the real scene, and then the color shadow correction is performed on the image. However, the color temperature information in the real scene is very complicated, and it is impossible to obtain all color temperature correction parameters in advance through experiments. Based on this, the accuracy of the existing color shading correction method is low.

Summary of the invention

The embodiments of the present application provide a color correction method, a terminal device, a chip, and a computer-readable storage medium to solve the problem of low accuracy of the existing color shading correction.

In the first aspect, an embodiment of the present application provides a color shading correction method. First, an image to be corrected is acquired; then, based on pre-calibrated color shading data, the color shading correction is performed on the image to be corrected, and the color shading data includes Color shading data for at least two monochromatic lights.

It can be seen that the embodiment of the present application performs color shading correction on the image by using the color shading data of a variety of monochromatic light, effectively covering the color shading forms in various color temperature scenes, and improving the accuracy of color shading correction.

In a possible implementation of the first aspect, based on pre-calibrated color shading data, performing color shading correction on the image to be corrected includes:

After dividing the image to be corrected into first image blocks, obtain the pixel statistical value of each of the first image blocks;

After converting the pixel statistical value of each of the first image blocks from the first color space to the second color space, the pixel value of the target channel of the image to be corrected in the second color space is obtained, and the target channel Is a channel that is not related to brightness, and the second color space is a color space that is not related to brightness;

According to the pre-calibrated color shading data and the pixel value of the target channel, the color shading correction is performed on the image to be corrected.

It should be noted that the image to be corrected is divided into multiple first image blocks, and the pixel statistical values of the first image blocks are used to represent the image blocks, which can effectively reduce the amount of calculation. In addition, converting the pixel statistical value of the first image block to the second color space independent of the brightness can reduce or avoid the influence of the brightness on the color value, so as to further improve the accuracy of the color shading correction.

In a possible implementation manner of the first aspect, the method further includes:

Determine the main color of the image to be corrected according to the pixel statistical value of each of the first image blocks, and obtain the pixel position of the pixel corresponding to the main color;

According to the pre-calibrated color shading data and the pixel value of the target channel, performing color shading correction on the image to be corrected includes:

Performing color shadow estimation according to the pixel position, the color shadow data, and the pixel value of the target channel to obtain the color shadow matrix of each target channel of the image to be corrected;

Using the color shadow matrix of the target channel, perform color shadow correction on the image to be corrected.

It should be noted that using the pixel position of the main color in the image to be corrected is used to perform color shading correction on the image, rather than using a specific color for color shading correction, which can avoid inaccurate color shadow estimation due to the lack of specific colors as much as possible To further improve the accuracy of color shading correction.

In a possible implementation of the first aspect, color shadow estimation is performed according to the pixel position, the color shadow data, and the pixel value of the target channel to obtain the color shadow of each target channel of the image to be corrected The matrix includes:

Obtaining the initial color shadow matrix of each target channel according to the pixel position, the color shadow data, and the pixel value of the target channel;

Perform an expansion operation on the initial color shadow matrix to obtain the color shadow matrix of each target channel of the image to be corrected.

In a possible implementation of the first aspect, obtaining the initial color shadow matrix of each target channel according to the pixel position, the color shadow data, and the pixel value of the target channel includes:

Using the base of each target channel extracted from the color shadow data to calculate the weight coefficient of the initial color shadow matrix of each target channel according to the pixel position and the pixel value of the target channel;

According to the basis of each target channel and the weight coefficient, the initial color shadow matrix of each target channel is obtained.

It should be noted that using the base of color shadow data for shadow correction, compared to using all color shadow data for shadow correction, the former can effectively reduce the storage space requirements of the algorithm.

In a possible implementation of the first aspect, using the color shadow matrix of the target channel to perform color shadow correction on the image to be corrected includes:

Multiply the color shadow matrix of each target channel by the corresponding pixel value of the target channel of the image to be corrected in the second color space to obtain the corrected image in the second color space;

The corrected image in the second color space is converted to a target color space to obtain a corrected image in the target color space, where the target color space is the first color space or the third color space.

In a possible implementation manner of the first aspect, after acquiring the image to be corrected, the method further includes:

Performing image preprocessing on the image to be corrected;

After dividing the image to be corrected into first image blocks, obtaining the pixel statistical value of each first image block includes:

After the image to be corrected after image preprocessing is divided into first image blocks, the pixel statistical value of each first image block is obtained.

In a possible implementation manner of the first aspect, before acquiring the image to be corrected, the method further includes:

Obtain the gray board images under N kinds of monochromatic light respectively, where N is a positive integer greater than or equal to 2;

Perform image preprocessing on the gray board image;

Dividing the pre-processed gray board image into second image blocks, and obtaining the pixel statistical value of each second image block;

After the pixel statistical value of each second image block is converted from the fourth color space to the fifth color space, the pixel value of the target channel of the gray board image in the fifth color space is obtained, and the fifth The color space is a color space that has nothing to do with brightness;

The color shading data is obtained based on the pixel values of the target channel of the gray panel image of the N monochromatic lights.

In a possible implementation of the first aspect, after obtaining the color shading data based on the pixel values of the target channel of the gray panel image of the N monochromatic lights, the method further includes:

The base of each target channel is extracted from the color shading data.

In a possible implementation of the first aspect, the monochromatic light is monochromatic light in the visible light range.

In a possible implementation of the first aspect, after dividing the image to be corrected into first image blocks, obtaining the pixel statistical value of each first image block includes:

Meshing the image to be corrected to obtain the first image block;

The average value of pixels of each of the first image blocks is counted, and the average value of pixels is used as the pixel statistical value of the first image block.

In a second aspect, an embodiment of the present application provides a terminal device including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The processor executes the computer program when the computer program is executed. A method as described in any one of the first aspect above.

In a third aspect, an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned first aspect is implemented. method.

In a fourth aspect, an embodiment of the present application provides a chip that includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the computer program, the implementation is as follows: The method of any one of the above-mentioned first aspects.

In a fifth aspect, embodiments of the present application provide a computer program product, which when the computer program product runs on a terminal device, causes the terminal device to execute the method described in any one of the foregoing first aspects.

It is understandable that, for the beneficial effects of the second aspect to the fifth aspect described above, reference may be made to the relevant description in the first aspect described above, and details are not repeated here.

Description of the drawings

FIG. 1 is a schematic diagram of acquiring image data through a camera module provided by an embodiment of the application;

2 is a block diagram of a part of the structure of a mobile phone provided by an embodiment of the application;

FIG. 3 is a schematic diagram of the software structure of the mobile phone 200 according to an embodiment of the application;

FIG. 4 is a schematic block diagram of the flow of a color shading correction method provided by an embodiment of the application

FIG. 5 is a schematic block diagram of another flow of a color shading correction method provided by an embodiment of the application;

FIG. 6 is a schematic diagram of a method for dividing a gray board graph provided by an embodiment of the application;

FIG. 7 is a schematic block diagram of another flow of the color shading correction method provided by an embodiment of the application;

FIG. 8 is a schematic block diagram of the flow of a spectrum calibration process provided by an embodiment of the application;

FIG. 9 is a schematic diagram of a color shading correction process provided by an embodiment of the application;

FIG. 10 is a schematic block diagram of the structure of a color shading correction device provided by an embodiment of the application.

Detailed ways

In the following description, for the purpose of illustration rather than limitation, specific details such as a specific system structure and technology are proposed for a thorough understanding of the embodiments of the present application.

The color shading correction solution provided by the embodiments of the present application can be applied to a terminal device that integrates a camera module and has a shooting function. The camera module generally includes a lens, an infrared cut-off filter, and an image sensor. The lens is generally composed of one or more lenses. The image sensor may generally be a CCD image sensor or a CMOS image sensor. For the process of capturing image data by the terminal device through the camera module, refer to the schematic diagram of image data acquired through the camera module shown in FIG. 1.

As shown in FIG. 1, after light passes through the lens 11 and the infrared cut filter 12 in sequence, it reaches the image sensor 13, and the image sensor 13 converts the light signal into an electrical signal to collect image data. In this process, after the light is refracted by the lens 11, the angle will change. The light transmittance of the infrared cut filter changes with the incident angle, that is, the light of the same wavelength, the incident angle is different, the transmittance will be correspondingly different, which causes the problem of color shadows in the captured image.

Color shading generally has the following characteristics: the same camera module has different color shading expressions at different color temperatures; the same color temperature may have different spectrums, resulting in the same color temperature may also have different color shading forms.

Specifically, light at the same color temperature may have different spectra, that is, light of the same color may be composed of different monochromatic lights. For example, a certain color of light may be composed of three monochromatic lights of A, B, and C, or it may be composed of three monochromatic lights of A, D, and E.

Based on this, if you obtain all the color shadow correction parameters corresponding to the color temperature through experiments in advance, and establish a one-to-one correspondence between the color temperature and the color shadow correction parameters; then, in actual application, find the corresponding color according to the color temperature of the current light source Shadow correction parameters, and then use the color shadow correction parameters for correction, the color temperature spectrum in the actual application stage and the color temperature spectrum in the experimental stage may be different, and the problem of inaccurate color shadow correction may occur. For example, in the experimental stage, the spectrum of a certain color temperature includes three monochromatic lights of A, B, and C, while in the actual application stage, the spectrum of this color temperature includes three monochromatic lights of A, D, and E. At this time, under the same color temperature, the color shading form in the experimental phase and the color shading form in the actual application phase are different, resulting in inaccurate color correction.

In the embodiment of the present application, the color shading correction is performed by pre-calibrated color shading data of various monochromatic spectrums, which can effectively cover the color shading forms appearing in various color temperature scenes, thereby improving the accuracy of the color shading correction.

In the embodiment of this application, the camera module is integrated, and the type of terminal device with the shooting function can be any type. The terminal device can be but not limited to a mobile phone, a tablet computer, a notebook computer, a netbook or a personal digital assistant, etc., which is wrong here. The specific type of terminal equipment is limited.

The terminal device may specifically include at least one processor, a memory, and a computer program that is stored in the memory and can run on the at least one processor. When the processor executes the computer program, each of the color shading correction methods provided in the embodiments of the present application is implemented. step.

The processor can be a central processing unit (Central Processing Unit, CPU), the processor can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like. The memory may be an internal storage unit of the terminal device in some embodiments. In other embodiments, it may also be an external storage device of the terminal device.

Further, the memory may also include both an internal storage unit of the terminal device and an external storage device. The memory is used to store the operating system, application programs, boot loader (BootLoader), data and other programs, such as program codes of computer programs. The memory can also be used to temporarily store data that has been output or will be output.

In addition, the terminal device may also include, but is not limited to, a lens, an infrared cut-off filter, an image sensor, a DSP chip, a display, an input and output device, etc.

As an example and not a limitation, taking the terminal device as a mobile phone as an example, FIG. 2 shows a block diagram of a part of the structure of the mobile phone provided in the embodiment of the present application. Referring to FIG. 2, the mobile phone may include: a radio frequency (RF) circuit 210, a memory 220, an input unit 230, a display unit 240, a sensor 250, an audio circuit 260, a wireless fidelity (WiFi) module 270, a processing 280, power supply 290 and other components. Those skilled in the art can understand that the structure of the mobile phone shown in FIG. 2 does not constitute a limitation on the mobile phone, and may include more or less components than those shown in the figure, or a combination of some components, or different component arrangements.

The following describes the components of the mobile phone in detail with reference to Figure 2:

The RF circuit 210 can be used for receiving and sending signals during information transmission and communication or during a call. In particular, after receiving the downlink information of the base station, it is processed by the processor 280; in addition, the designed uplink data is sent to the base station. Generally, the RF circuit includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier (LNA), a duplexer, and the like. In addition, the RF circuit 210 can also communicate with the network and other devices through wireless communication. The above-mentioned wireless communication can use any communication standard or protocol, including but not limited to Global System of Mobile Communication (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (Code Division) Multiple Access (CDMA), Wideband Code Division Multiple Access (WCDMA), Long Term Evolution (LTE), Email, Short Messaging Service (SMS), etc.

The memory 220 may be used to store software programs and modules. The processor 280 executes various functional applications and data processing of the mobile phone by running the software programs and modules stored in the memory 220. The memory 220 may mainly include a program storage area and a data storage area. The program storage area may store an operating system, an application program required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; Data created by the use of mobile phones (such as audio data, phone book, etc.), etc. In addition, the memory 220 may include a high-speed random access memory, and may also include a non-volatile memory, for example, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

The input unit 230 may be used to receive inputted number or character information, and generate key signal input related to user settings and function control of the mobile phone 200. Specifically, the input unit 230 may include a touch panel 231 and other input devices 232. The touch panel 231, also called a touch screen, can collect the user's touch operations on or near it (for example, the user uses any suitable objects or accessories such as fingers, stylus, etc.) on the touch panel 231 or near the touch panel 231. Operation), and drive the corresponding connection device according to the preset program. Optionally, the touch panel 231 may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch position, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into contact coordinates, and then sends it To the processor 280, and can receive and execute the commands sent by the processor 280. In addition, the touch panel 231 can be implemented in multiple types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 231, the input unit 230 may also include other input devices 232. Specifically, other input devices 232 may include, but are not limited to, one or more of a physical keyboard, function keys (such as volume control buttons, switch buttons, etc.), trackball, mouse, joystick, and the like.

The display unit 240 may be used to display information input by the user or information provided to the user and various menus of the mobile phone. The display unit 240 may include a display panel 241. Optionally, the display panel 241 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an organic light emitting diode (Organic Light-Emitting Diode, OLED), etc. Further, the touch panel 231 can cover the display panel 241. When the touch panel 231 detects a touch operation on or near it, it transmits it to the processor 280 to determine the type of the touch event, and then the processor 280 responds to the touch event. The type provides corresponding visual output on the display panel 241.

Although in FIG. 2, the touch panel 231 and the display panel 241 are used as two independent components to realize the input and input functions of the mobile phone, but in some embodiments, the touch panel 231 and the display panel 241 may be integrated. Realize the input and output functions of the mobile phone.

The mobile phone 200 may also include at least one sensor 250, such as a light sensor, a motion sensor, an image sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. The ambient light sensor can adjust the brightness of the display panel 241 according to the brightness of the ambient light. The proximity sensor can close the display panel 241 and/or when the mobile phone is moved to the ear. Or backlight. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in various directions (usually three-axis), and can detect the magnitude and direction of gravity when it is stationary. It can be used to identify mobile phone posture applications (such as horizontal and vertical screen switching, related Games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, percussion), etc. The image sensor can convert light signals into electrical signals to collect image data. Of course, the mobile phone can also include a lens and an infrared cut-off filter that cooperate with the image sensor to complete image data collection.

In addition, the mobile phone can also be equipped with other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc., which will not be repeated here.

The audio circuit 260, the speaker 261, and the microphone 262 can provide an audio interface between the user and the mobile phone. The audio circuit 260 can transmit the electrical signal converted from the received audio data to the speaker 261, and the speaker 161 converts it into a sound signal for output. On the other hand, the microphone 262 converts the collected sound signals into electrical signals, which are received by the audio circuit 260 and converted into audio data, and then processed by the audio data output processor 280, and sent to, for example, another mobile phone via the RF circuit 210. Or output the audio data to the memory 220 for further processing.

WiFi is a short-distance wireless transmission technology. The mobile phone can help users send and receive emails, browse web pages, and access streaming media through the WiFi module 270. It provides users with wireless broadband Internet access. Although FIG. 2 shows the WiFi module 270, it is understandable that it is not a necessary component of the mobile phone 200 and can be omitted as needed without changing the essence of the invention.

The processor 280 is the control center of the mobile phone. It uses various interfaces and lines to connect various parts of the entire mobile phone. It executes by running or executing software programs and/or modules stored in the memory 220 and calling data stored in the memory 220. Various functions and processing data of the mobile phone can be used to monitor the mobile phone as a whole. Optionally, the processor 280 may include one or more processing units; preferably, the processor 280 may integrate an application processor and a modem processor, where the application processor mainly processes the operating system, user interface, application programs, etc. , The modem processor mainly deals with wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 280.

For example, after the mobile phone collects image data through the lens, infrared cut filter and image sensor, the processor obtains the image data, and then performs image preprocessing, image block processing, and conversion to brightness-independent image data. The steps of chromaticity space, determining the main color of the image data, color shading estimation and color shading correction are used to correct the collected image data with color shading problems, obtain the corrected image, and display the corrected image Display on the screen.

The mobile phone 200 also includes a power source 290 (such as a battery) for supplying power to various components. Preferably, the power source may be logically connected to the processor 280 through a power management system, so that functions such as charging, discharging, and power consumption management can be managed through the power management system.

Although not shown, the mobile phone 200 may also include a camera. Optionally, the position of the camera on the mobile phone 200 may be front or rear, which is not limited in the embodiment of the present application.

Optionally, the mobile phone 200 may include a single camera, a dual camera, or a triple camera, etc., which is not limited in the embodiment of the present application. For example, the mobile phone 200 may include three cameras, of which one is a main camera, one is a wide-angle camera, and one is a telephoto camera. The lens generally includes one or more convex lenses.

Optionally, when the mobile phone 200 includes multiple cameras, the multiple cameras may be all front-mounted, or all rear-mounted, or partly front-mounted and another part rear-mounted, which is not limited in the embodiment of the present application.

After introducing the hardware components of the mobile phone, the software structure of the mobile phone 200 will be introduced below.

FIG. 3 is a schematic diagram of the software structure of the mobile phone 200 according to an embodiment of the present application. Taking the mobile phone 200 operating system as the Android system as an example, in some embodiments, the Android system is divided into four layers, namely the application layer, the application framework layer (framework, FWK), the system layer, and the hardware abstraction layer. The communication between the layers is through a software interface.

As shown in Fig. 3, the application layer can be a series of application packages, which can include applications such as short message, calendar, camera, video, navigation, gallery, and call.

The application framework layer provides an application programming interface (application programming interface, API) and a programming framework for applications in the application layer. The application framework layer may include some predefined functions, such as functions for receiving events sent by the application framework layer.

As shown in Figure 3, the application framework layer can include a window manager, a resource manager, and a notification manager.

The window manager is used to manage window programs. The window manager can obtain the size of the display screen, determine whether there is a status bar, lock the screen, take a screenshot, etc. The content provider is used to store and retrieve data and make these data accessible to applications. The data may include videos, images, audios, phone calls made and received, browsing history and bookmarks, phone book, etc.

The resource manager provides various resources for the application, such as localized strings, icons, pictures, layout files, video files, and so on.

The notification manager enables the application to display notification information in the status bar, which can be used to convey notification-type messages, and it can automatically disappear after a short stay without user interaction. For example, the notification manager is used to notify download completion, message reminders, and so on. The notification manager can also be a notification that appears in the status bar at the top of the system in the form of a chart or a scroll bar text, such as a notification of an application running in the background, or a notification that appears on the screen in the form of a dialog window. For example, text messages are prompted in the status bar, prompt sounds, electronic devices vibrate, and indicator lights flash.

The application framework layer can also include:

A view system, the view system includes visual controls, for example, controls that display text, controls that display pictures, and so on. The view system can be used to build applications. The display interface can be composed of one or more views. For example, a display interface that includes a short message notification icon may include a view that displays text and a view that displays pictures.

The phone manager is used to provide the communication function of the mobile phone 200. For example, the management of the call status (including connecting, hanging up, etc.).

The system layer can include multiple functional modules. For example: sensor service module, physical state recognition module, 3D graphics processing library (for example: OpenGL ES), etc.

The sensor service module is used to monitor the sensor data uploaded by various sensors at the hardware layer and determine the physical state of the mobile phone 200;

Physical state recognition module, used to analyze and recognize user gestures, faces, etc.;

The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, synthesis, and layer processing.

The system layer can also include:

The surface manager is used to manage the display subsystem and provides a combination of 2D and 3D layers for multiple applications.

The media library supports playback and recording of a variety of commonly used audio and video formats, as well as still image files. The media library can support multiple audio and video encoding formats, such as MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

The hardware abstraction layer is the layer between hardware and software. The hardware abstraction layer can include display drivers, camera drivers, sensor drivers, etc., used to drive related hardware at the hardware layer, such as display screens, cameras, sensors, and so on.

It should be noted that FIGS. 2 and 3 are only examples of terminal devices. When the terminal device is a tablet computer or other device, the related introduction can be referred to the corresponding content in FIG. 2 and FIG. 3, which will not be repeated here.

After introducing the possible situations of the terminal device of the embodiment of the present application, the color shading correction solution provided by the embodiment of the present application will be described in detail below.

In the embodiment of the present application, the color shading correction scheme may include a spectrum calibration stage and a practical stage. The spectrum calibration stage is the process of indexing the color shading data of various monochromatic lights. The practical stage refers to the process of using the calibrated color shading data to perform color shading correction on the image after the color shading data of various monochromatic lights are calibrated. .

Refer to FIG. 4, which is a schematic block diagram of the flow of a color shading correction method provided by an embodiment of this application. The process may specifically refer to the color shading correction process in the practical stage. The method can include the following steps:

Step S401: Obtain an image to be corrected.

It is understandable that the terminal device can obtain the image to be corrected by shooting through an integrated camera module, so as to obtain the above-mentioned image to be corrected. The camera module integrated in the terminal device generally includes a lens, an infrared cut filter, and an image sensor. Of course, the image to be corrected may also be an image collected in advance through a terminal integrated with a camera module. In this case, the image to be corrected may be obtained by reading the pre-stored image.

The image to be corrected refers to an image that needs color shading correction. The image is generally taken by a terminal integrated with a camera module, and the image generally has a problem of color shading.

Step S402: Perform color shading correction on the image to be corrected based on the pre-calibrated color shading data, the color shading data includes color shading data of at least two monochromatic lights.

It should be noted that the aforementioned pre-calibrated color shading data includes at least two color shading data of monochromatic light. Optionally, monochromatic light includes all monochromatic light in the visible light range. In general, the more monochromatic light, the more color temperature scenes covered, and the better the color shading correction effect.

In specific applications, the process of performing color shading correction based on the color shading data of a variety of monochromatic light may specifically include: first performing image preprocessing on the image to be corrected, and then performing image segmentation on the image to be corrected after image preprocessing, to obtain multiple Image blocks, and count the pixel statistics of each image block, and use the pixel statistics as the pixel value of the image block; then, the pixel statistics of the image block can be converted to a color space that has nothing to do with brightness, and record that has nothing to do with brightness Then, the main color of the image to be corrected can be determined, and the pixel position of the corresponding pixel of the main color can be obtained; finally, according to the value of the channel independent of the brightness, the color shading data of a variety of monochromatic lights and the main The color corresponds to the pixel position of the pixel. The color shading is estimated first to obtain the color shading matrix, and then the color shading matrix is used for color shading correction to obtain a corrected image.

It should be noted that, in some embodiments, the image to be corrected may not be divided into blocks, but the entire image to be corrected may be directly processed. However, the entire image to be corrected has a large amount of data and a large amount of calculation. In comparison, the image to be corrected is divided into blocks and then processed, which can reduce the amount of calculation.

In some embodiments, the pixel position of the pixel corresponding to the main color may not be used for color shading estimation, but a specific color may be used for color shading estimation. In comparison, the former can avoid as much as possible the problem of inaccuracy of color shading estimation due to the lack of specific colors, thereby further improving the accuracy of color shading correction.

In some embodiments, the base of each channel extracted from the color shading data can be used for color shading estimation, which can effectively reduce the storage space requirements of the algorithm compared to using all the color shading data for color shading correction. Of course, in some other embodiments, image preprocessing may not be performed on the image to be corrected.

It can be seen that the embodiment of the present application performs color shading correction on the image by using the color shading data of a variety of monochromatic light, effectively covering the color shading forms in various color temperature scenes, and improving the accuracy of the color shading correction.

Referring to FIG. 5, which shows a schematic block diagram of another flow of the color shading correction method provided by the embodiment of the present application, the method may include the following steps:

Step S501: Obtain an image to be corrected.

Step S502: After dividing the to-be-corrected image into first image blocks, the pixel statistical value of each first image block is obtained.

In specific applications, due to the large width and height of the image to be corrected, more pixels, and a large amount of data, in order to reduce the amount of calculation, the image to be corrected is divided into blocks to divide the image to be corrected into multiple first ones. The image block, and the pixel statistical value of the first image block is used to represent the image block.

The image division method can be grid division, circular division, or other division methods. Refer to the schematic diagram of the gray board map division method shown in Fig. 6, as shown in Fig. 6, the gray board map on the left side of Fig. 6 uses a grid division method, and the gray board map on the right side of Fig. 6 uses a circular division.

It should be noted that the above-mentioned pixel statistical value may be the pixel average value or the median value. Specifically, after the image to be corrected is divided into blocks and M first image blocks are obtained, the pixel statistical values of the M first image blocks are respectively counted, and the pixel statistical values are used to represent the corresponding first image blocks.

For example, a grid division method is used to perform block processing on the image to be corrected to obtain M first image blocks. Based on the pixel value of each pixel in the first image block, the average pixel value of each image block is counted, and the pixel average value is used as the pixel statistical value of the first image block, that is, the pixel average value is used to represent the pixels of the first image block Value, each first image block corresponds to a pixel average value.

Step S503: After the pixel statistical value of each first image block is converted from the first color space to the second color space, the pixel value of the target channel of the image to be corrected in the second color space is obtained, and the target channel is brightness-independent Channel, the second color space is a color space that has nothing to do with brightness.

It should be noted that the first color space refers to the color space where the image to be corrected is originally located, and the first color space may be, for example, RGB or RYB. The second color space refers to a color space that has nothing to do with brightness, and the color space may be, for example, but not limited to HSV, HSI, Lab, or YCrCb. The target channel refers to a channel that is not related to brightness in the second color space. For example, when the second color space is HSV, the channel that is not related to brightness (that is, the target channel) includes the H channel and the S channel. For another example, when the second color space is YCrCb, channels that are not related to brightness (ie, target channels) include Cr channels and Cb channels.

Converting the pixel value of the image to be corrected to the second color space that is not related to brightness can avoid or reduce the impact of brightness on color values.

After converting the pixel value of the first image block to the second color space, the pixel value of the channel independent of the brightness can be recorded. For example, when the second color space is HSV, the channels that are not related to brightness (ie, the target channel) include the H channel and the S channel, and the pixel values of the H channel and the S channel are recorded. For another example, when the second color space is YCrCb, and the channels that are not related to brightness (ie, the target channel) include the Cr channel and the Cb channel, the pixel values of the Cr channel and the Cb channel are recorded.

Step S504: Perform color shading correction on the image to be corrected according to the pre-calibrated color shading data and the pixel value of the target channel.

It should be noted that when there are N types of monochromatic spectra, the number of target channels is denoted as C, and the number of first image blocks is denoted as M, the pre-calibrated color shading data can include N*C*M data.

In specific applications, all color shading data, that is, N*C*M data, can be used for color shading correction. But saving N*C*M data requires a lot of storage space. At this time, in order to reduce the storage space requirements of the algorithm, the base extracted from the color shading data can be used for color shading correction. Specifically, corresponding to each channel, k representative values are extracted from the N*M data as the base of the color shading data of the channel. After extracting the base of each target channel, the extracted base can be used to represent the pixel value of the target channel in any color space.

In specific applications, specific colors can be used for color shading correction. However, in some cases, there may be a lack of the specific color, resulting in inaccurate color shading correction. At this time, the main color of the image to be corrected can be determined first, and the pixel position of the pixel corresponding to the main color can be recorded, and the color shading correction is performed based on the pixel position, so as to improve the accuracy of the color shading correction.

Specifically, the color shadow estimation can be performed first according to the pre-calibrated color shadow data and the pixel value of the target channel to obtain the color shadow matrix of the image to be corrected. Then, use the color shading matrix for color shading correction.

Referring to FIG. 7 shows a schematic block diagram of another flow of the color shading correction method provided by the embodiment of the present application, the method may include the following steps:

Step S701: Obtain an image to be corrected.

Step S702: After dividing the image to be corrected into first image blocks, obtain the pixel statistical value of each first image block.

Optionally, after acquiring the image to be corrected, the method further includes: performing image preprocessing on the image to be corrected. At this time, the image to be corrected after image preprocessing may be divided into first image blocks, and then the pixel statistical value of each first image block can be obtained.

The image preprocessing may include, but is not limited to, initial stage image processing operations such as black level correction and white balance.

Step S703: After converting the pixel statistical value of each first image block from the first color space to the second color space, the pixel value of the target channel of the image to be corrected in the second color space is obtained, and the target channel is brightness-independent Channel, the second color space is a color space that has nothing to do with brightness.

It should be noted that the above steps S701 to S703 are the same as the above steps S501 to S503. For related introduction, please refer to the corresponding content above, which will not be repeated here.

Step S704: Determine the main color of the image to be corrected according to the pixel statistical value of each first image block, and obtain the pixel position of the pixel corresponding to the main color.

It should be noted that the main color of the image to be corrected refers to the color with the largest number of pixels in the image to be corrected. After the main color of the image to be corrected is determined, the pixel position of the pixel corresponding to the main color is recorded.

For example, if the number of red pixels in the image to be corrected is the largest, it is determined that the main color of the image to be corrected is red. And record the pixel position of the red pixel.

In specific applications, clustering or threshold segmentation can be used to determine the main color of the image to be corrected.

Step S705: Perform color shadow estimation according to the pixel position, the color shadow data and the pixel value of the target channel to obtain the color shadow matrix of each target channel of the image to be corrected.

In specific applications, the initial color shadow matrix of each target channel can be estimated first, and then the initial color shadow matrix can be amplified to obtain the aforementioned color shadow matrix. Step S705 may specifically include the following two steps.

The first step: According to the pixel position, the color shadow data and the pixel value of the target channel, the initial color shadow matrix of each target channel is obtained.

It is understandable that all the color shading data can be used for color shading correction, or the base of color shading data can be used for color shading correction.

In some embodiments, the base of each target channel extracted from the color shading data may be used to calculate the weight coefficient of the initial color shading matrix of each target channel according to the pixel position and the pixel value of the target channel. Then, according to the basis and weight coefficient of each target channel, the initial color shadow matrix of each target channel is obtained.

Specifically, the value of the pixel corresponding to the main color of the c-th target channel in the second color space is denoted as Q _c , and the weight coefficient of the initial color shading matrix is calculated by the following formula 1.

Among them, {B ₁ ,B ₂ ,B ₃ ,...,B _K } refers to the base of the C-th target channel. {a ₁ ,a ₂ ,a ₃ ,...,a _K } refers to the weight coefficient of the initial color shading matrix. Ω={(x,y)} refers to the pixel position of the corresponding pixel of the main color.

Solving the above formula (1), the weight coefficient of the initial color shadow matrix of each target channel is obtained, namely {a ₁ , a ₂ , a ₃ ,..., a _K }. Then, get the initial color shading matrix of each target channel through the following formula 2.

S _r =a ₁ B ₁ +a ₂ B ₂ +a ₃ B ₃ +...+a _k B _k (2)

Among them, S _r refers to the initial color shadow matrix of the target channel.

The second step: expand the initial color shadow matrix to obtain the color shadow matrix of each target channel of the image to be corrected.

It should be noted that _{the size of S r} is the result of reducing the size, so it needs to be enlarged to the size of the original image to be corrected. The method of amplification can be, but is not limited to, bilinear interpolation. After amplification, take the reciprocal of each value to get the final color shadow matrix of each target channel.

It should be noted that the use of the pixel position of the main color in the image to be corrected is used to estimate the color shadow of the image, instead of using a specific color to estimate the color shadow, it can avoid the inaccurate color shadow estimation due to the lack of specific colors as much as possible To further improve the accuracy of color shading correction.

Step S706: Use the color shadow matrix of the target channel to perform color shadow correction on the image to be corrected.

Specifically, first, the color shading matrix of each target channel is respectively multiplied by the corresponding pixel value of the target channel of the image to be corrected in the second color space to obtain the corrected image in the second color space; then, the second color space is The corrected image of is converted to the target color space to obtain a corrected image in the target color space, where the target color space is the first color space or the third color space.

Wherein, the above-mentioned third color space may be a color space related to brightness, for example, the third color space is RYB or RGB. In other words, the corrected image in the second color space can be converted back to the original color space of the image to be corrected (that is, the first color space), or it can be converted back to a color space that is different from the original color space of the image to be corrected ( That is, the third color space).

For example, the first color space of the image to be corrected is RGB, and the second color space is HSV. At this time, after the corrected image of HSV is obtained, the corrected image in HSV color space can be converted to RGB color space to complete color shading correction .

After introducing the corresponding process of the practical phase of color shading correction, the following will introduce the spectral calibration phase.

Referring to the schematic block diagram of the flow of the spectrum calibration process shown in FIG. 8, the process may include:

Step S801: Obtain gray panel images under N types of monochromatic light, where N is a positive integer greater than or equal to 2.

Specifically, a narrow-band light source or a laser can be used to generate monochromatic light in the visible wavelength range, for example, from 380nm to 780nm, each Tnm generates a monochromatic light source, and then the terminal device with integrated camera module is used to photograph each monochromatic light. Gray board diagram under shaded light. The gray board image obtained by shooting may be a gray board image as shown in FIG. 6.

Step S802: Perform image preprocessing on the gray board image.

It can be understood that image preprocessing includes but is limited to operations such as black level correction and white balance.

Step S803: Divide the preprocessed gray board image into second image blocks, and obtain the pixel statistical value of each second image block.

It should be noted that the second image block refers to the image block corresponding to the gray plate image in the spectral calibration stage. The image division method can be grid division or circular division as shown in FIG. 6. After the image is divided into blocks, the pixel statistics of each second image block are calculated, and the pixel statistics may be the average value or the median of the pixels. The pixel statistical value of each second image block is used to represent the pixel value of the second image block.

Step S804: After the pixel statistical value of each second image block is converted from the fourth color space to the fifth color space, the pixel value of the target channel of the gray plate image in the fifth color space is obtained, and the fifth color space is the same as the brightness Irrelevant color space.

It should be noted that the fourth color space refers to the color space where the grayboard image is originally located, and the fifth color space refers to a color space that has nothing to do with brightness, which can be equivalent to the second color space above. The target channel refers to a channel that has nothing to do with brightness.

Step S805: Obtain color shading data based on the pixel values of the target channel of the gray panel image of the N types of monochromatic light.

For example, there are N types of monochromatic lights, the number of target channels is C, and the data of the second image block is M, then the color shading data may include N*C*M data.

In some embodiments, N*C*M pieces of data can be used directly for color shading correction, but a large amount of storage space is required. In other embodiments, in order to reduce the storage space requirement of the algorithm, a small number of bases can be extracted from N*C*M data, and the bases can be used for color shading correction.

Optionally, the method further includes: step S806, extracting the base of each target channel from the color shading data.

Specifically, for each target channel, k representative values are extracted from N*M data as the base of the target channel. The method of extracting the basis can be but not limited to dimensionality reduction or clustering. For example, methods such as PCA (Principal Component Analysis) or K-means are used to extract k representative values from N*M data.

For example, for the c-th channel, the extracted basis is

The value of the image on the c-th channel can be expressed as:

Among them, {a ₁ ,a ₂ ,a ₃ ,...,a _K } are the weight coefficients.

In other words, the value of the target channel in any color space can be expressed as a combination of bases.

In order to better introduce the color shading correction method provided by the embodiments of the present application, the following will be combined with the schematic diagram of the color shading correction process shown in FIG. 9.

As shown in Figure 9, it includes a spectrum calibration stage and a practical stage. In the spectral calibration stage, the camera module integrated in the terminal device collects image data under N types of monochromatic light, and then performs image preprocessing, image block processing, conversion to brightness-independent chromaticity space, and recording color. Extraction of the value and basis of the chroma channel in the degree space. Wherein, the chromaticity space is the same as the above-mentioned second color space, and the chromaticity space may be, for example, but not limited to, color spaces such as HSV, HIS, or YCrCb. The chroma channel refers to the channel that is not related to the brightness in the image to be corrected, and can be equivalent to the target channel above. Base extraction refers to extracting the base of each target channel from the color shading data.

In the practical stage, the terminal equipment collects the image data in the real scene through the integrated camera module, and then performs image preprocessing on the image data, image block processing, and conversion to a chromaticity space independent of brightness to determine the main color of the image And obtain the pixel position of the main color corresponding to the pixel, and then use the base extracted in the spectral calibration stage to estimate the color shadow to obtain the color shadow matrix of the image, and finally use the color shadow matrix to perform color shadow correction to obtain the corrected image.

It can be seen that using the color shadow data of N types of monochromatic light for color shadow correction can effectively cover the color shadow forms in various color temperature scenes, and improve the accuracy of color shadow correction. Further, extracting the base in the color shading data and using the base to perform color shading correction can effectively reduce the storage space requirements of the algorithm. Further, using the position of the main color corresponding pixel in the image to perform color shadow estimation can improve the accuracy of color shadow estimation, thereby improving the accuracy of color shadow correction.

Corresponding to the color shading correction method of the above embodiment, FIG. 10 shows a schematic block diagram of the structure of the color shading correction device provided in an embodiment of the present application. For ease of description, only the parts related to the embodiment of the present application are shown.

Referring to FIG. 10, the device may include:

The obtaining module 101 is used to obtain an image to be corrected.

The color shading correction module 102 is configured to perform color shading correction on the image to be corrected based on pre-calibrated color shading data. The color shading data includes color shading data of at least two monochromatic lights.

In a possible implementation manner, the aforementioned color shading correction module may include:

The image block unit is used to divide the to-be-corrected image into first image blocks to obtain the pixel statistical value of each first image block.

The color space conversion unit is used to convert the pixel statistical value of each first image block from the first color space to the second color space to obtain the pixel value of the target channel of the image to be corrected in the second color space, where the target channel is For channels that are not related to brightness, the second color space is a color space that is not related to brightness.

The color shading correction unit is used to perform color shading correction on the image to be corrected according to the pre-calibrated color shading data and the pixel value of the target channel.

In a possible implementation manner, the above-mentioned device may further include a main color pixel position obtaining module, configured to determine the main color of the image to be corrected according to the pixel statistical value of each first image block, and obtain the pixel points corresponding to the main color Pixel position;

The aforementioned color shading correction unit is specifically used for:

Perform color shadow estimation according to the pixel position, color shadow data and the pixel value of the target channel to obtain the color shadow matrix of each target channel of the image to be corrected;

Use the color shadow matrix of the target channel to perform color shadow correction on the image to be corrected.

In a possible implementation manner, the above-mentioned color shading correction unit is specifically used for:

According to the pixel position, color shadow data and the pixel value of the target channel, the initial color shadow matrix of each target channel is obtained;

The initial color shadow matrix is expanded to obtain the color shadow matrix of each target channel of the image to be corrected.

Further, the above-mentioned color shading correction unit is specifically used for:

Using the base of each target channel extracted from the color shadow data, calculate the weight coefficient of the initial color shadow matrix of each target channel according to the pixel position and the pixel value of the target channel;

According to the basis and weight coefficient of each target channel, the initial color shadow matrix of each target channel is obtained.

Multiply the color shadow matrix of each target channel with the corresponding pixel value of the target channel of the image to be corrected in the second color space to obtain the corrected image in the second color space;

The corrected image in the second color space is converted to the target color space to obtain the corrected image in the target color space, and the target color space is the first color space or the third color space.

In a possible implementation manner, the foregoing device may further include:

Image preprocessing module, used to perform image preprocessing on the image to be corrected;

The above-mentioned image block unit is specifically used for:

In a possible implementation manner, the foregoing apparatus may further include:

Spectral calibration module, used to obtain gray board images under N kinds of monochromatic light, N is a positive integer greater than or equal to 2; preprocess the gray board images; divide the gray board images after image preprocessing into the first Two image blocks, and the pixel statistical value of each second image block is obtained; after the pixel statistical value of each second image block is converted from the fourth color space to the fifth color space, the gray board image under the fifth color space is obtained The fifth color space is a color space that has nothing to do with brightness; based on the pixel values of the target channel of the gray plate image of the N monochromatic light, the color shading data is obtained.

In a possible implementation manner, the above-mentioned spectral calibration module is also used to extract the base of each target channel from the color shading data.

In a possible implementation manner, the monochromatic light is monochromatic light in the visible light range.

In a possible implementation, the above-mentioned image block unit is specifically used to: perform grid division on the image to be corrected to obtain the first image block; count the average value of the pixels of each first image block, and use the average value of the pixels as the first image block. The pixel statistics of an image block.

The above-mentioned color shading correction device has the function of realizing the above-mentioned color shading correction method. This function can be realized by hardware or by executing corresponding software by hardware. The hardware or software includes one or more modules corresponding to the above-mentioned functions. Is software and/or hardware.

It should be noted that the information interaction and execution process between the above-mentioned devices/modules are based on the same concept as the method embodiments of this application, and their specific functions and technical effects can be found in the method embodiments. I won't repeat it here.

Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the division of the above functional units and modules is used as an example. In practical applications, the above functions can be allocated to different functional units and modules as needed. Module completion, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist alone physically, or two or more units can be integrated into one unit. The above-mentioned integrated units can be hardware-based Formal realization can also be realized in the form of a software functional unit. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the present application. For the specific working process of the units and modules in the foregoing system, reference may be made to the corresponding process in the foregoing method embodiment, which will not be repeated here.

The embodiments of the present application also provide a computer-readable storage medium, and the computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps in the foregoing method embodiments can be realized.

An embodiment of the present application also provides a chip, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The processor implements the method in any one of the foregoing method embodiments when the processor executes the computer program.

The embodiments of the present application provide a computer program product. When the computer program product runs on a terminal device, the terminal device can realize the steps in the foregoing method embodiments when executed.

If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on this understanding, the implementation of all or part of the processes in the above-mentioned embodiment methods in the present application can be accomplished by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When executed by the processor, the steps of the foregoing method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying the computer program code to the photographing device/terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), and random access memory (RAM, Random Access Memory), electric carrier signal, telecommunications signal and software distribution medium. For example, U disk, mobile hard disk, floppy disk or CD-ROM, etc. In some jurisdictions, according to legislation and patent practices, computer-readable media cannot be electrical carrier signals and telecommunication signals.

In the above-mentioned embodiments, the description of each embodiment has its own focus. For parts that are not described in detail or recorded in an embodiment, reference may be made to related descriptions of other embodiments.

A person of ordinary skill in the art may realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraint conditions of the technical solution. Professionals and technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered beyond the scope of this application.

In the embodiments provided in this application, it should be understood that the disclosed device and method may be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, for example, multiple units or components may be divided. It can be combined or integrated into another system, or some features can be ignored or not implemented. In addition, the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.

The above-mentioned embodiments are only used to illustrate the technical solutions of the present application, not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, a person of ordinary skill in the art should understand that it can still implement the foregoing The technical solutions recorded in the examples are modified, or some of the technical features are equivalently replaced; these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the application, and should be included in Within the scope of protection of this application.

Claims

A color shading correction method, characterized in that it comprises:

Obtain the image to be corrected;

Based on the pre-calibrated color shading data, perform color shading correction on the image to be corrected, and the color shading data includes color shading data of at least two monochromatic light.
8. The method of claim 1, wherein, based on pre-calibrated color shading data, performing color shading correction on the image to be corrected comprises:

After dividing the image to be corrected into first image blocks, obtain the pixel statistical value of each of the first image blocks;

After converting the pixel statistical value of each of the first image blocks from the first color space to the second color space, the pixel value of the target channel of the image to be corrected in the second color space is obtained, and the target channel Is a channel that is not related to brightness, and the second color space is a color space that is not related to brightness;

According to the pre-calibrated color shading data and the pixel value of the target channel, the color shading correction is performed on the image to be corrected.
The method according to claim 2, wherein the method further comprises:

Determine the main color of the image to be corrected according to the pixel statistical value of each of the first image blocks, and obtain the pixel position of the pixel corresponding to the main color;

According to the pre-calibrated color shading data and the pixel value of the target channel, performing color shading correction on the image to be corrected includes:

Performing color shadow estimation according to the pixel position, the color shadow data, and the pixel value of the target channel to obtain the color shadow matrix of each target channel of the image to be corrected;

Using the color shadow matrix of the target channel, perform color shadow correction on the image to be corrected.
The method of claim 3, wherein the color shadow estimation is performed according to the pixel position, the color shadow data, and the pixel value of the target channel to obtain the color shadow of each target channel of the image to be corrected The matrix includes:

Obtaining the initial color shadow matrix of each target channel according to the pixel position, the color shadow data, and the pixel value of the target channel;

Perform an expansion operation on the initial color shadow matrix to obtain the color shadow matrix of each target channel of the image to be corrected.
The method of claim 4, wherein obtaining the initial color shadow matrix of each target channel according to the pixel position, the color shadow data, and the pixel value of the target channel comprises:

Using the base of each target channel extracted from the color shadow data to calculate the weight coefficient of the initial color shadow matrix of each target channel according to the pixel position and the pixel value of the target channel;

According to the basis of each target channel and the weight coefficient, the initial color shadow matrix of each target channel is obtained.
The method according to claim 3, wherein, using the color shadow matrix of the target channel to perform color shadow correction on the image to be corrected comprises:

Multiply the color shadow matrix of each target channel by the corresponding pixel value of the target channel of the image to be corrected in the second color space to obtain the corrected image in the second color space;

The corrected image in the second color space is converted to a target color space to obtain a corrected image in the target color space, where the target color space is the first color space or the third color space.
The method according to claim 2, characterized in that, after acquiring the image to be corrected, the method further comprises;

Performing image preprocessing on the image to be corrected;

After dividing the image to be corrected into first image blocks, obtaining the pixel statistical value of each first image block includes:

After the image to be corrected after image preprocessing is divided into first image blocks, the pixel statistical value of each first image block is obtained.
The method according to any one of claims 1 to 7, characterized in that, before acquiring the image to be corrected, the method further comprises:

Obtain the gray board images under N kinds of monochromatic light respectively, where N is a positive integer greater than or equal to 2;

Perform image preprocessing on the gray board image;

Dividing the pre-processed gray board image into second image blocks, and obtaining the pixel statistical value of each second image block;

After the pixel statistical value of each second image block is converted from the fourth color space to the fifth color space, the pixel value of the target channel of the gray board image in the fifth color space is obtained, and the fifth The color space is a color space that has nothing to do with brightness;

The color shading data is obtained based on the pixel values of the target channel of the gray panel image of the N monochromatic lights.
The method according to claim 8, wherein after obtaining the color shading data based on the pixel values of the target channel of the gray panel image of the N monochromatic lights, the method further comprises:

The base of each target channel is extracted from the color shading data.
3. The method according to claim 2, wherein after dividing the image to be corrected into first image blocks, obtaining the pixel statistical value of each first image block comprises:

Meshing the image to be corrected to obtain the first image block;

The average value of pixels of each of the first image blocks is counted, and the average value of pixels is used as the pixel statistical value of the first image block.
A terminal device, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program as claimed in claims 1 to 10. The method of any one of.
A chip comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program as claimed in claims 1 to 10 Any of the methods.
A computer-readable storage medium storing a computer program, wherein the computer program implements the method according to any one of claims 1 to 10 when the computer program is executed by a processor.