Pixel parasitic light sensitivity effect suppression method and image sensor
By calculating the pixel signal intensity of each row in the multi-frame basic image and performing parasitic light correction, the problem of suppressing pixel parasitic light sensitivity effect is solved, and the image quality is significantly improved.
Patent Information
- Application Number
- CN202411695057.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-25
- Publication Date
- 2025-02-25
AI Technical Summary
The prior art is difficult to effectively suppress the pixel parasitic light sensitivity effect, especially in the global shutter mode, resulting in a decline in image quality.
By acquiring the basic images of multiple frames, calculating the signal intensity of each row of pixels, obtaining the reference value of the full picture, and using these values to calculate the parasitic light correction coefficient of each row of pixels, and finally performing line-by-line parasitic light correction on the original image.
It effectively suppresses the parasitic light sensitivity effect, improves image quality, eliminates random noise, and ensures the consistency of the image.
Smart Images
Figure CN119521028A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of image processing, and in particular to a method for suppressing pixel parasitic light sensitivity effect and an image sensor. Background Art
[0002] With the widespread use of image sensors in various application scenarios, such as mobile photography, machine vision, autonomous driving, and security monitoring, image quality has become one of the important factors affecting the performance of these application systems. Among them, the global shutter technology can capture the light signals of all pixels in the image at the same time, reducing or eliminating the image distortion problem that is common in high-speed motion scenes.
[0003] However, due to the complexity of the internal structure and circuit design of the pixel array in the image sensor, some parasitic light (non-ideal light response in the image sensor) is mistaken for a valid signal during the photoelectric conversion process, resulting in uneven brightness or color in the output image, which is the parasitic light sensitivity effect (PLS). The parasitic light sensitivity effect is particularly prominent in the global shutter mode, because in the global shutter mode, all pixels capture light and read out signals at the same time, causing the parasitic light to generate uneven noise in the entire image, seriously affecting the image quality.
[0004] Existing methods for suppressing parasitic light sensitivity effects mainly rely on the design and optimization of hardware shielding layers. However, due to the limitations of the manufacturing process, existing methods for suppressing parasitic light sensitivity effects are difficult to completely eliminate the parasitic light sensitivity effect. Especially under complex lighting conditions or in high dynamic range scenes, the parasitic light sensitivity effect is more significant and cannot be eliminated by a single hardware method, affecting image quality. Summary of the invention
[0005] The object of the present invention is to provide a method for suppressing the parasitic light sensitivity effect of a pixel and an image sensor, so as to solve the problem of how to effectively suppress the parasitic light sensitivity effect to improve the image quality.
[0006] In order to solve the above technical problems, the present invention provides a method for suppressing the parasitic light sensitivity effect of a pixel, comprising: Obtain multiple frames of basic images; Calculating the signal strength of each row of pixels using the multiple frames of basic images; According to the signal strength of each row of pixels, the whole image benchmark value is obtained; The parasitic light correction coefficient of each row of pixels is calculated by using the full image reference value and the signal strength of each row of pixels; The parasitic light correction coefficient is used to perform parasitic light correction on the input original image.
[0007] Optionally, in the method for suppressing pixel parasitic photosensitivity effect, the base image is an image with uniform illumination.
[0008] Optionally, in the method for suppressing the pixel parasitic photosensitivity effect, the step of calculating the signal intensity of each row of pixels using the multiple frames of basic images to obtain a signal intensity data set includes: Obtain the signal value of each pixel in each frame of the basic image to obtain a signal data set; Based on the signal data set, the signal intensity of each row of pixels is calculated; The signal strength of each row of pixels is counted to obtain the signal strength data set.
[0009] Optionally, in the method for suppressing the pixel parasitic light sensitivity effect, the step of calculating the signal strength of each row of pixels based on the signal data set includes: In the signal data set, the average of the signal values of the pixels in the same row in the same frame of the basic image is calculated to obtain the signal reference value of each row of pixels in the frame of the basic image; The signal strength of each row of pixels is obtained by calculating the average of the signal reference values of the pixels in the same row in multiple frames of basic images.
[0010] Optionally, in the method for suppressing the pixel parasitic light sensitivity effect, the calculating the signal strength of each row of pixels by using the multiple frames of basic images further includes: Count the signal strength of each row of pixels to obtain a signal strength data set; The signal strength dataset is stored.
[0011] Optionally, in the method for suppressing the pixel parasitic light sensitivity effect, obtaining the full image reference value according to the signal strength of each row of pixels includes: The average signal strength of each row of pixels is calculated to serve as the full image reference value.
[0012] Optionally, in the method for suppressing the pixel parasitic light sensitivity effect, the parasitic light correction coefficient of each row of pixels is calculated by using the full image reference value and the signal intensity of each row of pixels, including: The ratio of the whole image reference value to the signal intensity of each row of pixels is used as the parasitic light correction coefficient of the row of pixels.
[0013] Optionally, in the method for suppressing the pixel parasitic light sensitivity effect, performing parasitic light correction on the input original image using the parasitic light correction coefficient includes: Input original image; Obtaining the pixel value of each pixel in the original image; The pixel value of the current pixel is corrected using the parasitic light correction coefficient of the row where the current pixel is located to obtain a corrected pixel value.
[0014] Optionally, in the method for suppressing the pixel parasitic light sensitivity effect, the step of correcting the pixel value of the current pixel point using the parasitic light correction coefficient of the row where the current pixel point is located to obtain a corrected pixel value includes: The pixel value of the current pixel point in the original image is multiplied by the parasitic light correction coefficient to obtain a corrected pixel value.
[0015] In order to solve the above technical problems, the present invention also provides an image sensor, comprising a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the method for suppressing the parasitic photosensitivity effect of pixels as described in any one of the above items is executed.
[0016] The method for suppressing the pixel parasitic light sensitivity effect and the image sensor provided by the present invention include: acquiring multiple frames of basic images; calculating the signal strength of each row of pixels using the multiple frames of basic images; obtaining a full-image reference value according to the signal strength of each row of pixels; calculating the parasitic light correction coefficient of each row of pixels using the full-image reference value and the signal strength of each row of pixels; and performing parasitic light correction on the input original image using the parasitic light correction coefficient. By calculating the parasitic light correction coefficient corresponding to each row using the signal strength of each row of the multiple frames of basic images, the parasitic light correction coefficient of each row can be used to perform parasitic light correction on the input original image row by row, thereby effectively suppressing the parasitic light sensitivity effect in a dynamic correction manner. At the same time, since the parasitic light correction is performed row by row, the random noise in the signal of the current row of pixels can also be eliminated, thereby ensuring the consistency of the image, improving the image quality, and solving the problem of how to effectively suppress the parasitic light sensitivity effect to improve the image quality. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 A flow chart of a method for suppressing pixel parasitic light sensitivity effect provided in this embodiment; Figure 2 A schematic diagram of the arrangement of image pixels provided in this embodiment. DETAILED DESCRIPTION
[0018] The following is a further detailed description of the method for suppressing the pixel parasitic light sensitivity effect and the image sensor proposed in the present invention in combination with the accompanying drawings and specific embodiments. It should be noted that the accompanying drawings are all in a very simplified form and use non-precise proportions, which are only used to conveniently and clearly assist in explaining the purpose of the embodiments of the present invention. In addition, the structure shown in the accompanying drawings is often a part of the actual structure. In particular, the emphasis that each drawing needs to show is different, and sometimes different proportions are used.
[0019] It should be noted that the terms "first", "second", etc. in the specification, claims and drawings of the present invention are used to distinguish similar objects in order to describe the embodiments of the present invention, rather than to describe a specific order or sequence. It should be understood that the structures used in this way can be interchanged under appropriate circumstances. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0020] This embodiment provides a method for suppressing the parasitic light sensitivity effect of a pixel. Figure 1 As shown, including: S1, obtain multiple frames of basic images; S2, calculating the signal intensity of each row of pixels using the multiple frames of basic images to obtain a signal intensity data set; S3, obtaining the whole image reference value according to the signal strength of each row of pixels; S4, calculating the parasitic light correction coefficient of each row of pixels by using the full image reference value and the signal strength of each row of pixels; S5, performing parasitic light correction on the input original image using the parasitic light correction coefficient.
[0021] The method for suppressing the parasitic light sensitivity effect of pixels provided in the present embodiment calculates the parasitic light correction coefficient corresponding to each row by utilizing the signal intensity of each row of the multi-frame basic images, so that the parasitic light correction coefficient of each row can be utilized to perform parasitic light correction on the input original image row by row, thereby effectively suppressing the parasitic light sensitivity effect in a dynamic correction manner. At the same time, since the parasitic light correction is performed row by row, the random noise in the signal of the pixel in the current row can also be eliminated, thereby ensuring the consistency of the image, improving the image quality, and solving the problem of how to effectively suppress the parasitic light sensitivity effect to improve the image quality.
[0022] It should be noted that this embodiment takes into account that existing image sensors usually read out and process pixel data in a row readout manner, so when performing parasitic light correction, each row of pixels is selected as the correction basis. When a column readout method is selected to read and process pixel data, a person skilled in the art should understand that when performing parasitic light correction using the method for suppressing the pixel parasitic light sensitivity effect provided by the present application, each column of pixels should be selected as the correction basis to ensure that the parasitic light can be correctly and effectively eliminated while the pixel data can be read out normally. . Row and column replacement without violating the main purpose of the present application should fall within the scope of protection of the present application.
[0023] Specifically, in this embodiment, in step S1, a plurality of frames of basic images are obtained, wherein the basic images are images with uniform illumination, and the format is not limited to RAW images, RGB images or YUV images.
[0024] like Figure 2 As shown, the basic image is an image including M rows and N columns of pixels, wherein the coordinates of each pixel can be expressed as (i, j), i represents the row where the pixel is located, j represents the column where the pixel is located, i=1,2,...,M, j=1,2,...,N.
[0025] In practical applications, a backplane with uniform illumination can be used as the shooting object, and multiple images can be taken using an image sensor to obtain a basic image. The multiple frames of basic images can be obtained by continuous shooting or interval shooting. However, it should be noted that in order to ensure that the results obtained by subsequent calculations are correct and consistent, the brightness of the uniform illumination corresponding to the multiple frames of basic images here should be consistent, so as to avoid deviations in calculation results caused by inconsistent light brightness.
[0026] Furthermore, in this embodiment, in step S2, the method of calculating the signal strength of each row of pixels using the multiple frames of basic images to obtain a signal strength data set includes: S21, obtaining the signal value of each pixel in each frame of the basic image to obtain a signal data set.
[0027] Among them, the method for obtaining the signal value of each pixel is well known to those skilled in the art, and this application will not repeat it. In this embodiment, the signal value of the pixel is also referred to as the pixel value. The signal value of each pixel is recorded as FS(p,i,j), where p represents the p-th frame basic image, i represents the i-th row, and j represents the j-th column; the signal value of each pixel of all basic images is counted to obtain a signal data set, which is recorded as FS.
[0028] S22: Calculate the signal intensity of each row of pixels based on the signal data set.
[0029] First, in the signal data set, the mean value of the signal values of the same row of pixels in the same frame of the basic image is calculated to obtain the signal reference value of each row of pixels in the frame of the basic image, that is, the signal reference value ARD ( i) can be expressed as:
[0030] Then, the average of the signal reference values of the same row of pixels in the multiple frames of the basic image is calculated to obtain the signal strength of each row of pixels. That is, the signal strength AR(i) of each row of pixels can be expressed as:
[0031] Wherein, K represents the total number of frames of the acquired basic image.
[0032] In this way, through a simple mean calculation, the signal value of each pixel point of each frame of the basic image can be used to calculate the signal strength of each row of pixels. In this embodiment, by performing mean calculation on the pixel signal values of multiple frames of basic images, the signal value deviation caused by slight changes in each shooting environment (such as image sensor current, voltage, shooting environment brightness, temperature and humidity, etc.) can be effectively reduced, and the random noise of the signal value can be reduced, thereby enhancing the stability of the signal and ensuring the accuracy of the calculated signal strength, thereby eliminating the influence of random noise on the parasitic light correction calculation, and improving the effectiveness and accuracy of suppressing the parasitic light sensitivity effect.
[0033] Of course, in practical applications, you can also choose to use a weighted average method to obtain the signal strength of each row of pixels according to actual conditions. For example, set the weights of several pixels close to the center pixel to be larger, and the farther away from the center pixel, the smaller the weight of the pixel signal value, thereby performing a weighted average calculation.
[0034] Also, in practical applications, if the image pixel size is too large, several spaced pixel points in the same row or several pixel points located in the center can be extracted at a certain ratio to perform mean calculation or weighted average calculation, thereby effectively reducing the amount of calculation.
[0035] Preferably, in order to facilitate the call of data in the subsequent parasitic light correction process, in this embodiment, the method of calculating the signal intensity of each row of pixels using the multiple frames of basic images to obtain a signal intensity data set in step S2 also includes: S23, counting the signal strength of each row of pixels to obtain a signal strength data set. That is, summing up the signal strengths AR(i) of all row pixels to obtain a signal strength data set, which is recorded as AR.
[0036] S24: Store the signal strength data set AR.
[0037] Furthermore, in this embodiment, in step S3, a full-image reference value is obtained according to the signal strength of each row of pixels.
[0038] Specifically, in this embodiment, the average signal strength of each row of pixels is obtained as the full image reference value, that is, the full image reference value is recorded as GA, and the calculation method of the full image reference value can be expressed as:
[0039] Where M is the total number of pixel rows in the base image.
[0040] And, in this embodiment, in step S4, the parasitic light correction coefficient of each row of pixels is calculated using the full image reference value and the signal strength of each row of pixels.
[0041] Specifically, in this embodiment, the ratio of the whole image reference value to the signal intensity of each row of pixels is used as the parasitic light correction coefficient of the row of pixels, that is, the parasitic light correction coefficient of the i-th row of pixels is denoted as AF(i), and the calculation method of the parasitic light correction coefficient of the i-th row of pixels can be expressed as:
[0042] In this way, the parasitic light correction coefficient corresponding to each row of pixels can be obtained by simply averaging and proportioning. The parasitic light correction coefficient corresponding to the current pixel point can then be used to suppress the parasitic light sensitivity effect of the current pixel point, which can effectively eliminate the parasitic light sensitivity effect and its cumulative impact.
[0043] Furthermore, in this embodiment, in step S5, the method of performing parasitic light correction on the input original image using the parasitic light correction coefficient includes: S51, input the original image.
[0044] Specifically, the input original image should be an image captured by the image sensor used to obtain the basic image, and the size of the original image should also be consistent with the size of the basic image.
[0045] S52, obtaining the pixel value of each pixel in the original image.
[0046] The method of obtaining pixel values is well known to those skilled in the art, and will not be described in detail in this application. The pixel value here is equivalent to the signal value of the pixel point.
[0047] S53, correcting the pixel value of the current pixel point using the parasitic light correction coefficient of the row where the current pixel point is located to obtain a corrected pixel value.
[0048] Specifically, in this embodiment, the pixel value of the current pixel point in the original image may be multiplied by the parasitic light correction coefficient to obtain a corrected pixel value, that is, the corrected pixel value is expressed as:
[0049] in, Represents the corrected pixel value of the pixel with coordinates (i, j). Represents the original pixel value of the pixel with coordinates (i, j). Indicates the parasitic light correction coefficient for the same row as the pixel with coordinates (i, j).
[0050] Since the signal values (pixel values) of the pixels used in the whole process of calculating the parasitic light correction coefficient are all greater than or equal to 0, the obtained parasitic light correction coefficient is greater than 0. In this way, after the parasitic light correction is performed on the input original image, there is no need to perform negative number truncation processing, which effectively simplifies the calculation, reduces the calculation complexity and system power consumption.
[0051] The method for suppressing the pixel parasitic light sensitivity effect provided in this embodiment takes into account the relationship between parasitic light and pixel readout time, that is, during a long readout process, the influence of parasitic light will accumulate, and the first row of data and the last row of data read out of the entire image are inconsistently affected by parasitic light. Therefore, this embodiment performs parasitic light pollution correction on the pixel points of each row, which can effectively eliminate the parasitic light sensitivity effect and its cumulative influence. At the same time, in the parasitic light pollution correction process, the signal data set is also preprocessed to eliminate the interference of random noise, so that the parasitic light correction coefficient corresponding to the pixel points of each row can be accurately obtained, ensuring the effect of suppressing parasitic light, effectively improving the phenomenon of uneven image brightness or poor consistency caused by the parasitic light sensitivity effect between rows in the image, and effectively improving the image quality.
[0052] This embodiment also provides an image sensor, including a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the method for suppressing the pixel parasitic photosensitivity effect as described above is executed.
[0053] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other. In addition, the different parts between the various embodiments can also be used in combination with each other, and the present invention is not limited to this.
[0054] The method for suppressing the pixel parasitic light sensitivity effect and the image sensor provided in the present embodiment include: acquiring multiple frames of basic images; calculating the signal strength of each row of pixels using the multiple frames of basic images; obtaining a full-image reference value based on the signal strength of each row of pixels; calculating the parasitic light correction coefficient of each row of pixels using the full-image reference value and the signal strength of each row of pixels; and performing parasitic light correction on the input original image using the parasitic light correction coefficient. By calculating the parasitic light correction coefficient corresponding to each row using the signal strength of each row of the multiple frames of basic images, the parasitic light correction coefficient of each row can be used to perform parasitic light correction on the input original image row by row, thereby effectively suppressing the parasitic light sensitivity effect in a dynamic correction manner. At the same time, since the parasitic light correction is performed row by row, the random noise in the signal of the current row of pixels can also be eliminated, thereby ensuring the consistency of the image, improving the image quality, and solving the problem of how to effectively suppress the parasitic light sensitivity effect to improve the image quality.
[0055] The above description is only a description of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any changes or modifications made by a person skilled in the art in the field of the present invention based on the above disclosure shall fall within the scope of protection of the claims.
Claims
1. A method for suppressing pixel parasitic light sensitivity effect, characterized in that: include: Acquire multiple frames of basic images; Calculating the signal strength of each row of pixels using the multiple frames of basic images; According to the signal strength of each row of pixels, the whole image benchmark value is obtained; The parasitic light correction coefficient of each row of pixels is calculated by using the full image reference value and the signal strength of each row of pixels; The parasitic light correction coefficient is used to perform parasitic light correction on the input original image.
2. The method for suppressing pixel parasitic light sensitivity effect according to claim 1, characterized in that: The basic image is an image with uniform illumination.
3. The method for suppressing pixel parasitic photosensitivity effect according to claim 1, characterized in that: The calculating the signal strength of each row of pixels by using the multiple frames of basic images includes: Obtain the signal value of each pixel in each frame of the basic image to obtain a signal data set; Based on the signal data set, the signal intensity of each row of pixels is calculated.
4. The method for suppressing pixel parasitic light sensitivity effect according to claim 3, characterized in that: The calculating the signal strength of each row of pixels based on the initial data set includes: In the signal data set, the average of the signal values of the pixels in the same row in the same frame of the basic image is calculated to obtain the signal reference value of each row of pixels in the frame of the basic image; The signal strength of each row of pixels is obtained by calculating the average of the signal reference values of the pixels in the same row in multiple frames of basic images.
5. The method for suppressing pixel parasitic light sensitivity effect according to claim 3, characterized in that: The calculating the signal strength of each row of pixels by using the multiple frames of basic images also includes: Count the signal strength of each row of pixels to obtain a signal strength data set; The signal strength dataset is stored.
6. The method for suppressing pixel parasitic light sensitivity effect according to claim 1, characterized in that: The whole image reference value is obtained according to the signal strength of each row of pixels, including: The average signal strength of each row of pixels is calculated to serve as the full image reference value.
7. The method for suppressing pixel parasitic light sensitivity effect according to claim 1, characterized in that: The method of calculating the parasitic light correction coefficient of each row of pixels by using the full image reference value and the signal strength of each row of pixels includes: The ratio of the whole image reference value to the signal intensity of each row of pixels is used as the parasitic light correction coefficient of the row of pixels.
8. The method for suppressing pixel parasitic light sensitivity effect according to claim 1, characterized in that: The using the parasitic light correction coefficient to perform parasitic light correction on the input original image includes: Input original image; Obtaining the pixel value of each pixel in the original image; The pixel value of the current pixel is corrected using the parasitic light correction coefficient of the row where the current pixel is located to obtain a corrected pixel value.
9. The method for suppressing pixel parasitic light sensitivity effect according to claim 8, characterized in that: The method of correcting the pixel value of the current pixel point by using the parasitic light correction coefficient of the row where the current pixel point is located to obtain a corrected pixel value includes: The pixel value of the current pixel point in the original image is multiplied by the parasitic light correction coefficient to obtain a corrected pixel value.
10. An image sensor, characterized in that: The invention comprises a memory, a processor and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the method for suppressing the parasitic light sensitivity effect of a pixel as described in any one of claims 1 to 9 is executed.