Disturbance correction method and apparatus for screen image data, storage medium

Abstract

The application provides a screen image data interference correction method and device and a storage medium. The method comprises the following steps: building a shooting environment; configuring target parameters required for shooting in the shooting environment, including light configuration parameters and camera configuration parameters; constructing a scene measurement model for the shooting environment, the input of the scene measurement model being at least part of the target parameters, and the output of the scene measurement model being first image data obtained by shooting a current screen; extracting a correction operator based on the scene measurement model; and when other screens are shot in the shooting environment and second image data is obtained, interference correction is performed on the second image data by using the correction operator. Based on the application, various noise interferences can be modeled and analyzed comprehensively, noise residual magnitudes can be controlled to a very low range, and the denoising effect is good. Even if other screens are replaced in the same shooting environment, noise interferences do not need to be measured and modeled again, and the operation efficiency can be improved.

Description

Technical Field

[0001] This application relates to the field of display technology, specifically to the field of screen detection technology, and particularly to a method, device, and storage medium for interference correction of screen image data. Background Technology

[0002] Capturing images of a screen in its display state and collecting data from these images is a crucial data source for analyzing screen characteristics, widely used in techniques such as screen Mura (brightness or color non-uniformity) detection and image enhancement. Currently, the mainstream method for acquiring screen image data is through shooting environments built using visual camera systems. However, during camera shooting, the shooting environment and process are often subject to noise interference from various factors, primarily from two aspects: firstly, noise interference caused by various ambient lights in the shooting environment; and secondly, noise interference caused by varying degrees of non-ideal characteristics of various electronic components in the shooting environment, such as uneven light emission from the screen backlight, inherent electronic noise in the camera, optical structural flaws in the camera lens design, and poor efficiency field uniformity of the camera's photosensitive element. These noise interferences all result in low-quality screen image data that cannot accurately reflect the true characteristics of the screen, severely impacting research on various display technologies supported by screen image data measurement and analysis.

[0003] To correct interference in screen image data, existing technologies attempt to incorporate a polarized light field into the visual camera system. This polarization process eliminates ambient light interference, extracting a clean transmitted light image of the screen as the data sample. However, this approach ignores non-ideal features introduced by factors such as camera noise and lens error, failing to comprehensively address the quality issues of the screen image data. If these ignored noises exceed a certain magnitude, even with polarization processing, the final screen image data still suffers from insufficient accuracy. Subsequent analysis of the screen image data cannot comprehensively model and analyze various noise interferences, resulting in often large residual noise levels after optimization and poor denoising performance. Furthermore, in this shooting environment, each interference correction requires modeling and analyzing the noise interference. For example, every time the screen being photographed is changed, the noise interference needs to be remeasured and modeled for correction, impacting operational efficiency. Summary of the Invention

[0004] In view of this, this application provides a method, device, and storage medium for interference correction of screen image data, which can improve the problem that it is difficult to completely eliminate noise interference, resulting in poor noise reduction effect, and that noise interference needs to be modeled and analyzed for each interference correction under the same shooting environment, thus affecting the operating efficiency.

[0005] This application provides a method for interference correction of screen image data, including: Set up the shooting environment, which includes at least a camera and a target surface for limiting the screen. Configure the target parameters required for shooting in the shooting environment, the target parameters including light configuration parameters and camera configuration parameters; A scene measurement model is constructed for the shooting environment. The input of the scene measurement model is at least a part of the target parameters, and the output is the first image data obtained by shooting the current screen. The correction operator is extracted based on the scene measurement model; When capturing images of other screens and obtaining second image data under the shooting environment, the second image data is subjected to interference correction by the correction operator.

[0006] Optionally, a scene measurement model is constructed for the shooting environment based on the following relationship: [(L1+ L2+ W1)×A1×G1×A2×G2+ S ] ×A3×G3+ N = I cap1 Where L1 is the ambient light intensity, L2 is the current screen sampling brightness, W1 is the light ripple noise introduced by the electrical characteristics of the current screen, A1 is the amplitude gain factor introduced by the camera lens, G1 is the light distortion matrix caused by the camera lens design, A2 is the efficiency factor of the energy amplitude of the photon signal received by the camera sensor, G2 is the conversion matrix of the camera sensor to convert photon signals into electrons, S is the camera's dark current signal, A3 is the camera's gain weighting factor, G3 is the conversion matrix of the camera to convert electrons into voltage signals, voltage signals into digital signals, and digital signals into first image data, N is the equivalent full-field white noise of the shooting environment, and I cap1 This refers to the first image data.

[0007] Optionally, the current screen is a liquid crystal display screen; the sampled brightness L2 of the current screen is obtained according to the following relationship: L2 = (L 21 + W2) × R Among them, L 21 W1 represents the current backlight brightness of the screen, W2 represents the current backlight ripple noise of the screen, and R represents the current screen's actual brightness transmittance.

[0008] Optionally, the current screen is an LED display screen; the sampled brightness L2 of the current screen is the brightness of the current screen.

[0009] Optionally, the camera is provided with a front-end circuit, a digital circuit, and an analog circuit; the sum of the gain factors of the front-end circuit, the digital circuit, and the analog circuit is used as the gain weighting factor A3 of the camera.

[0010] Optionally, the step of extracting the correction operator based on the scene measurement model includes: Obtain ideal image data I that reflects the true characteristics of the current screen. real ; The ideal image data I real With the first image data I cap1 The ratio of is used as a correction operator.

[0011] Optionally, the step of acquiring ideal image data I that reflects the true characteristics of the current screen... real ,include: A reference screen with uniform light emission brightness is photographed under the shooting environment to obtain a reference image; Calculate the average grayscale value of the target within the preset central area of ​​the reference image; Create an ideal image that has the same size as the reference image and whose average grayscale value at all pixel locations is the target average grayscale value; The image data of the ideal image is taken as the ideal image data I. real .

[0012] Optionally, the step of performing interference correction on the second image data using the correction operator includes: According to relation I cap20 = I cap2 × G correct The second image data is subjected to interference correction, wherein, I cap20 To interfere with the corrected image data, I cap2 For the second image data, G correct For the correction operator.

[0013] This application provides an interference correction device for screen image data, including a processor and a memory. The memory stores an interference correction program. When the interference correction program is executed by the processor, it implements the steps of the interference correction method for screen image data described above.

[0014] This application provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of any of the above-mentioned methods for correcting interference in screen image data.

[0015] As described above, this application incorporates both ambient light and camera configuration parameters into the interference correction of screen image data, enabling comprehensive modeling and analysis of various noise interferences. This keeps the noise residual magnitude extremely low, resulting in better noise reduction and a more accurate representation of the screen's true characteristics. Furthermore, through the constructed full-dimensional scene measurement model, this application can extract more purely reflective data of the screen's characteristics from the shooting environment. This data is more independent and pure, which is beneficial for improving the interference correction effect. In addition, the correction operator extracted based on the scene measurement model establishes a mapping relationship between the correction operator and the shooting environment. When shooting other screens and obtaining image data under the same shooting environment, interference correction can be performed using this correction operator without re-measuring noise interference or modeling and analyzing the re-measured noise interference, thereby improving operational efficiency. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating an embodiment of an interference correction method for screen image data according to this application. Figure 2 Ideal image data I of an embodiment of this application real A flowchart illustrating the method for obtaining [the data / method]. Figure 3 This is a grayscale distribution map of the uncorrected image obtained under the shooting environment of this application; Figure 4 Based on Figure 3 The grayscale span of the image shown in the grayscale distribution diagram; Figure 5 This is a grayscale distribution map of the image corrected using the method described in this application; Figure 6 Based on Figure 5 The grayscale span of the image shown in the grayscale distribution diagram; Figure 7 This is a schematic diagram of the structure of an interference correction device provided in an embodiment of this application. Detailed Implementation

[0017] To address the aforementioned problems in the prior art, this application provides a method, apparatus, and storage medium for interference correction of screen image data. These protection subjects are based on the same concept, and their problem-solving principles are essentially the same or similar. The implementation methods of each protection subject can be referred to mutually, and repeated details will not be elaborated.

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly described below in conjunction with specific embodiments and corresponding drawings. Obviously, the embodiments described below are only a part of the embodiments of this application, and not all of them. Unless otherwise specified, the following embodiments and their technical features can be combined with each other, and also belong to the technical solutions of this application.

[0019] Figure 1 This is a flowchart illustrating an embodiment of an interference correction method for screen image data according to this application. The interference correction method for screen image data can also be called a "method" or "interference correction method," used to comprehensively suppress interference in images captured from a screen, including noise cancellation and correction of systematic optical distortion. The execution entity for each step of the method can be a suitable interference correction device, a computer performing interference correction, or a storage medium, processor, controller, etc., with interference correction functionality.

[0020] Combined Figure 1 and Figure 2 As shown, the method includes at least the following steps S1 to S5.

[0021] S1: Set up the shooting environment, including at least the camera and the target surface used to limit the screen.

[0022] The shooting environment includes not only the instrument (e.g., a camera) and related components for fixing the instrument, but also the environmental conditions required for the camera to perform the shooting. Therefore, the shooting environment can also be considered as a shooting system that meets the requirements of the method, including both hardware such as the camera and the lighting conditions for providing light. This application does not limit the type of camera; for example, it can be an industrial camera commonly used in the art, and the shooting environment can be adapted to the specific type of camera.

[0023] In one example, this application can construct a darkroom using a simple mounting bracket and a non-reflective black cloth. The mounting bracket is used to fix an industrial camera and a target shooting surface within the darkroom. The target shooting surface defines the screen to be photographed. When the screen is fixed in the darkroom by the mounting bracket, the screen rests on the target shooting surface, with the light-emitting surface of the screen parallel to and facing away from the target shooting surface. Focusing tests are performed on the industrial camera based on the optimal viewing distance range to set an optimal shooting distance with a good blur range for the industrial camera, thereby fixing the relative positions of the industrial camera and the target shooting surface within the darkroom.

[0024] S2: Configure the target parameters required for shooting in the shooting environment, including light configuration parameters and camera configuration parameters.

[0025] In step S2, the shooting environment (e.g., a darkroom environment) and instrument characteristics need to be evaluated to configure the target parameters required for shooting, thereby ensuring that the performance and reliability of the environment and the instrument itself meet the accuracy requirements of measurement acquisition (i.e., acquiring screen image data). The light configuration parameters can be understood as the light parameters in the darkroom, and the camera configuration parameters refer to the camera's focal length, exposure parameters, etc.

[0026] In one example, this application can evaluate whether the relationship between the camera's shooting data values ​​and the excitation corresponds to the optimal linear region by adjusting the electrical parameters of the light source drive, the camera's lens aperture, and the camera's focal length, along with data such as camera viewing distance adjustment, camera gain, and exposure parameters, using a shooting data sampling method. The parameter matrix corresponding to the optimal linear region is then used as the optional configuration matrix value range for finally determining the target parameter. The implementation process of the shooting data sampling method can be found in existing technologies.

[0027] During the configuration of the target parameters, it is necessary to specifically evaluate the impact of ripple noise interference from the environment and instruments. This application can configure the target parameters by analyzing a dataset of test images collected under a certain parameter configuration to obtain the steady-state configuration value range boundary.

[0028] For example, when configuring the light configuration parameters, the impact of the screen's backlight electrical parameters on light emission uniformity, stability, or noise characteristics can be analyzed. Under a certain set of parameter configurations for the light source driving the backlight electrical parameters, image data of the screen is captured to obtain a test image dataset. For the test image dataset Modeling and analysis reveal that ripple noise interference exists when the drive current is too large. This ripple noise interference can be reduced or even eliminated by lowering the drive current to a certain steady-state configuration range. The optical configuration parameters are then configured based on the parameters corresponding to the elimination of ripple noise interference.

[0029] For example, when configuring the camera's settings, the effect of the camera's gain weighting factor on image quality or noise characteristics can be analyzed. A test image dataset is obtained under a certain set of parameter configurations. For the test image dataset Perform preliminary time filtering processing And construct a noise model , This represents the test image dataset. The first one obtained after preliminary processing by time filtering Zhang Image This represents the expected value calculation function, where n represents the number of sampled values, i.e., the number of images. Indicates noise results, for noise results Box plots are used for analysis to ensure the error magnitude is less than Δ, where Δ is a constant representing the set acceptable error magnitude. In one example, test image datasets are acquired by setting the camera gain to be off, digital gain to be on, and analog gain to be on, respectively. The corresponding error magnitudes are analyzed. Taking Δ as an example, if the error magnitude is less than Δ when camera gain is not enabled, it means that the shooting error requirements are met, and the camera configuration parameters can be configured based on not enabling camera gain. When only digital gain is enabled, if the error magnitude is less than Δ, it means that the shooting error requirements are met, and the camera configuration parameters can be configured based on only enabling digital gain. When only analog gain is enabled, if the error magnitude is greater than Δ, it means that the accuracy requirements are not met. The acquisition error of brightness information can be reduced by enhancing time filtering and time coherence integration, and the camera configuration parameters can be configured based on the corresponding parameters when the error magnitude is less than Δ.

[0030] S3: Construct a scene measurement model for the shooting environment. The input of the scene measurement model is at least a part of the target parameters, and the output is the first image data obtained by shooting the current screen.

[0031] Step S3 can be viewed as constructing a data model of optical signals to an image under the shooting environment. In one example, a scene measurement model is constructed for the shooting environment based on the following relationship: [(L1+ L2+ W1)×A1×G1×A2×G2+ S ] ×A3×G3+ N = I cap1 Where L1 is the ambient light intensity, L2 is the current screen sampling brightness, W1 is the light ripple noise introduced by the electrical characteristics of the current screen, A1 is the amplitude gain factor introduced by the camera lens, G1 is the light distortion matrix caused by the camera lens design, A2 is the efficiency factor of the energy amplitude of the photon signal received by the camera sensor, G2 is the conversion matrix of the camera sensor to convert photon signals into electrons, S is the camera's dark current signal, A3 is the camera's gain weighting factor, G3 is the conversion matrix of the camera to convert electrons into voltage signals, voltage signals into digital signals, and digital signals into first image data, N is the equivalent full-field white noise of the shooting environment, and I cap1 This refers to the first image data.

[0032] In actual shooting scenarios, cameras are equipped with front-end circuitry, digital circuitry, and analog circuitry. These circuits also affect the captured screen image data (including the first image data I). cap1Noise interference is generated, therefore the camera's gain weighting factor A3 is related to the gain factors of the front-end circuit, the digital circuit, and the analog circuit. Therefore, this application can use the sum of the gain factors of the front-end circuit, the digital circuit, and the analog circuit as the camera's gain weighting factor A3. That is, this application can obtain the camera's gain weighting factor A3 through the following relationship:

[0033] in, This represents the gain factor of the front-end circuit. This represents the gain factor of the digital circuit. This represents the gain factor of the analog circuit.

[0034] When the current screen is an LED display, the sampled brightness L2 of the current screen is the brightness of the current screen. However, when the current screen is an LCD display, the LCD requires backlighting to display images; therefore, the sampled brightness L2 of the current screen is related to the backlighting, and can be expressed by the formula L2 = (L... 21 + W2) × R, we get the current screen's sampled brightness L2, where L 21 Let W1 be the current backlight brightness of the screen, W2 be the current backlight ripple noise of the screen, and R be the current screen's actual brightness transmittance. Therefore, the constructed scene measurement model can be expressed as follows: [(L1+(L) 21 + W2) × R+ W1) × A1 × G1 × A2 × G2 + S ] × A3 × G3 + N = I cap1 S4: The correction operator is extracted based on the scene measurement model.

[0035] When the environmental interference noise L1, N and ripple noise W1, W2 are less than the control noise level, the noise terms can be considered negligible. Therefore, the relationship of the above scenario measurement model can be expressed as follows: L2× G1× A4× G4= I cap1 Where A4 is the equivalent weighted gain factor of the camera, obtained by equivalent calculation of A1, A2, and A3; G4 is the conversion matrix of the camera converting light into first image data, obtained by equivalent calculation of G2 and G3. The relationship can be understood as follows: the current screen brightness L2 passes through the lens shadow attenuation distortion matrix (i.e., the light distortion matrix caused by the camera's lens design) G1, to the camera's internal conversion operator A4 × G4, which converts light into image data, and then into first image data I. cap1 .

[0036] First image data I cap1 Even with the camera lens's shadow effects, the image data still cannot accurately reflect the true characteristics of the current screen. Image data acquired under the true characteristics of the current screen is considered ideal image data I. real And it manifests as: I real =L2×A4×G4, therefore this application can... real with I cap1 The mathematical relationship between them serves as the matrix for interference correction, i.e., the correction operator.

[0037] In step S4, the method for extracting the correction operator based on the scene measurement model can be: obtaining ideal image data I that reflects the true characteristics of the current screen. real The ideal image data I real With the first image data I cap1 The ratio of is used as a correction operator.

[0038] In one example, the ideal image data I is obtained. real In such a way, such as Figure 2 As shown, the process includes the following steps S41 to S44.

[0039] S41: Take a picture of a reference screen with uniform brightness under the shooting environment to obtain a reference image; S42: Calculate the average grayscale value of the target within the preset area at the center of the reference image; S43: Create an ideal image, the ideal image having the same size as the reference image, and the average gray value of all its pixel positions being the target average gray value; S44: Use the image data of the ideal image as the ideal image data.

[0040] A reference screen with uniform luminous brightness is the ideal luminous screen. When photographing the ideal luminous screen, the ideal image data I... real The brightness can be determined by the central area of ​​the image captured from the screen. In this example, the reference screen is photographed. As an ideal luminous screen, its own luminous brightness is uniform. The light emitted from the periphery of the screen will be attenuated to varying degrees after passing through the camera lens. Figure 3 and Figure 4 As shown, the final captured reference image and the first image data I cap1 Similarly, it exhibits a phenomenon where the center is bright and the edges are dark. Calculate the average grayscale value within the central area S of the reference image. An ideal image of the same size as the reference image is created using this brightness, wherein all pixel positions of the ideal image are grayscale. The image data of the ideal image Ideal image data The image data of the ideal image. With the first image data I cap1 The ratio G correct As a correction operator, it is independent of the screen being photographed and its brightness, which makes it applicable to any screen size and any brightness grayscale under the fixed shooting environment.

[0041] S5: When capturing images of other screens in the shooting environment and obtaining second image data, the second image data is subjected to interference correction by a correction operator.

[0042] According to relation I cap20 = I cap2 × G correct The second image data is subjected to interference correction, wherein, I cap20 To interfere with the corrected image data, I cap2 For the second image data, G correct For the correction operator. Corrected image data I cap20 Compared with the second image data before correction I cap2 Since the relationship is linear, the correction method provided by the relationship can be regarded as a linear correction method.

[0043] As described above, this application incorporates both ambient light and camera configuration parameters into the interference correction of screen image data, enabling comprehensive modeling and analysis of various noise interferences. This keeps the noise residual magnitude extremely low, resulting in better noise reduction and a more accurate representation of the screen's true characteristics. Furthermore, through the constructed full-dimensional scene measurement model, this application can extract more purely reflective data of the screen's characteristics from the shooting environment. This data is more independent and pure, which is beneficial for improving the interference correction effect. In addition, the correction operator extracted based on the scene measurement model establishes a mapping relationship between the correction operator and the shooting environment. When shooting other screens and obtaining image data under the same shooting environment, interference correction can be performed using this correction operator without re-measuring noise interference or modeling and analyzing the re-measured noise interference, thereby improving operational efficiency.

[0044] The correction operator extracted by the method of this application is only related to the shooting environment. After fixing the shooting environment, the correction operator can also be fixed and saved. The correction operator is completely independent of the specific brand or model of the screen and can be applied to different types of screens, including screens of various sizes, resolutions, and different brightness gray levels. The interference correction process of this application only needs to be performed once in the shooting environment, and the correction operator can be applied to other screens, which greatly improves the convenience and adaptability of operation.

[0045] In a real-world shooting environment, directly capturing a uniformly illuminated screen yields an uncorrected first image, whose grayscale distribution is as follows: Figure 3 and Figure 4 As shown, the image exhibits a bright center and dark edges, with the main grayscale distribution spanning 45 gray levels, a large deviation. The second image, obtained after interference correction using the method described in this application, has a grayscale distribution as follows: Figure 5 and Figure 6 As shown, the overall brightness is uniform, and the main grayscale distribution spans only 10 gray levels, which is more consistent with the true light-emitting characteristics of the screen, and the data is more accurate and effective.

[0046] This application embodiment also provides a storage medium storing an interference correction program, which is essentially a computer program, and when executed by a processor, implements the steps of the interference correction method for screen image data in any of the foregoing examples.

[0047] The storage medium includes, but is not limited to, any one of read-only memory (ROM), random access memory (RAM), magnetic disk, and optical disk.

[0048] Since the program stored in the storage medium can execute the steps in the interference correction method for screen image data of any embodiment provided in this application, the beneficial effects that the method of any of the foregoing embodiments can achieve can be realized. For details, please refer to the foregoing embodiments, which will not be repeated here.

[0049] This application also provides an interference correction device (hereinafter referred to as "interference correction device" or "device") and a chip for screen image data, both of which include a memory and a processor. The memory stores an interference correction program, which, when executed by the processor, implements the steps of the interference correction method for screen image data in any of the foregoing embodiments; and / or, the interference correction device or chip is provided with a storage medium as shown in the above example, and the processor loads the storage medium to execute the steps of the interference correction method for screen image data, thereby achieving the beneficial effects that the method of the corresponding embodiment can achieve.

[0050] Figure 7This is a schematic diagram of the structure of an interference correction device provided in an embodiment of this application. Figure 7 As shown, the interference correction device 70, which can also be called a screen image data interference correction device 70, includes: The acquisition module 71 is used to acquire the target parameters required for shooting in the established shooting environment, including light configuration parameters and camera configuration parameters. The model building module 72 is used to build a scene measurement model for the shooting environment based on the target parameters obtained by the acquisition module 71. The input of the scene measurement model is at least a part of the target parameters, and the output is the first image data obtained by shooting the current screen. The processing module 73 is used to extract a correction operator based on the scene measurement model constructed by the model construction module 72; and, when capturing images of other screens in the shooting environment and obtaining second image data, to perform interference correction on the second image data through the correction operator.

[0051] Through the cooperation of the above modules, interference correction of the screen image data is completed, thereby obtaining image data that can reflect the true characteristics of the screen.

[0052] It should be understood that the various modules of the interference correction device 70 can be represented as physical devices or virtual modules (i.e., commonly referred to as logical modules) in actual scenarios. A single module can be implemented by a single physical device or by two or more physical devices working together. Similarly, the function performed by a single module can be implemented by a single physical device or by two or more physical devices working together. Furthermore, the functions corresponding to each module can be implemented by the corresponding steps of the interference correction method for screen image data in any of the foregoing embodiments.

[0053] The above are only some embodiments of this application and do not limit the patent scope of this application. For those skilled in the art, any equivalent structural transformations made using the content of this specification and drawings are similarly included within the patent protection scope of this application.

[0054] The use of step designations such as S1 and S2 in this document is intended to more clearly and concisely describe the corresponding content and does not constitute a substantial restriction on the order. In specific implementation, those skilled in the art may execute S2 first and then S1, etc., but these should all be within the protection scope of this application.

[0055] Although this document uses terms such as "first," "second," etc., to describe various types of information, this information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. Furthermore, the singular forms "a," "an," and "the" are intended to also include the plural forms. The terms "or" and "and / or" are interpreted as inclusive, or meaning either one or any combination thereof. Exceptions to this definition only arise when combinations of elements, functions, steps, or operations are inherently mutually exclusive in some way.

Claims

1. A method for interference correction of screen image data, characterized in that, include: Set up the shooting environment, which includes at least a camera and a target surface for limiting the screen. Configure the target parameters required for shooting in the shooting environment, the target parameters including light configuration parameters and camera configuration parameters; A scene measurement model is constructed for the shooting environment. The input of the scene measurement model is at least a part of the target parameters, and the output is the first image data obtained by shooting the current screen. The correction operator is extracted based on the scene measurement model; When capturing images of other screens and obtaining second image data under the shooting environment, the second image data is subjected to interference correction by the correction operator.

2. The method according to claim 1, characterized in that, Based on the following relationship, a scene measurement model is constructed for the shooting environment: [(L1+ L2+ W1)×A1×G1×A2×G2+ S ] ×A3×G3+ N = I cap1 Where L1 is the ambient light intensity, L2 is the current screen sampling brightness, W1 is the light ripple noise introduced by the electrical characteristics of the current screen, A1 is the amplitude gain factor introduced by the camera lens, G1 is the light distortion matrix caused by the camera lens design, A2 is the efficiency factor of the energy amplitude of the photon signal received by the camera sensor, G2 is the conversion matrix of the camera sensor to convert photon signals into electrons, S is the camera's dark current signal, A3 is the camera's gain weighting factor, G3 is the conversion matrix of the camera to convert electrons into voltage signals, voltage signals into digital signals, and digital signals into first image data, N is the equivalent full-field white noise of the shooting environment, and I cap1 This refers to the first image data.

3. The method according to claim 2, characterized in that, The current screen is a liquid crystal display screen; the sampled brightness L2 of the current screen is obtained according to the following relationship: L2=(L 21 + W2)× R Among them, L 21 W1 represents the current backlight brightness of the screen, W2 represents the current backlight ripple noise of the screen, and R represents the current screen's actual brightness transmittance.

4. The method according to claim 2, characterized in that, The current screen is an LED display screen; the sampled brightness L2 of the current screen is the brightness of the current screen.

5. The method according to claim 2, characterized in that, The camera is equipped with front-end circuitry, digital circuitry, and analog circuitry. The sum of the gain factors of the front-end circuit, the digital circuit, and the analog circuit is used as the gain weighting factor A3 of the camera.

6. The method according to claim 3 or 4, characterized in that, The correction operator extracted based on the scene measurement model includes: Obtain ideal image data I that reflects the true characteristics of the current screen. real ; The ideal image data I real With the first image data I cap1 The ratio of is used as a correction operator.

7. The method according to claim 6, characterized in that, The ideal image data I that reflects the true characteristics of the current screen is obtained. real ,include: A reference screen with uniform light emission brightness is photographed under the shooting environment to obtain a reference image; Calculate the average grayscale value of the target within the preset central area of ​​the reference image; Create an ideal image that has the same size as the reference image and whose average grayscale value at all pixel locations is the target average grayscale value; The image data of the ideal image is taken as the ideal image data I. real .

8. The method according to claim 6, characterized in that, The interference correction of the second image data by the correction operator includes: According to relation I cap20 = I cap2 × G correct The second image data is subjected to interference correction, wherein, I cap20 To interfere with the corrected image data, I cap2 For the second image data, G correct For the correction operator.

9. An interference correction device for screen image data, characterized in that, The device includes a processor and a memory, the memory storing an interference correction program, which, when executed by the processor, implements the steps of the method according to any one of claims 1 to 8.

10. A storage medium, characterized in that, The device contains a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 8.

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