A composite correction method for spatial non-uniformity between pixels

Abstract

The application discloses a composite correction method for spatial non-uniformity between pixels and belongs to the technical field of semiconductors. The method is applied to a pixel array composed of composite medium grid photosensitive detectors, a light response curve model of each pixel is fitted according to the characteristics of the composite medium grid photosensitive detectors, data collected by the pixel array composed of the composite medium grid photosensitive detectors is corrected by adopting a multi-point uniform field correction method according to the light response curve model data, and a single-point correction method is adopted to correct abnormal conditions. The scheme can not only correct DRNU well, but also correct PRNU well, and can solve the problems of micro-light imaging in the light response curve of the composite medium grid photosensitive detector and nonlinearity when approaching full well, and further, the number of fitted segments and whether to discard abnormal conditions can be reduced or improved according to the cache capacity of the detector itself.

Description

TECHNICAL FIELD

[0001] The present application relates to a composite correction method for spatial non-uniformity between pixels, belonging to the technical field of semiconductors. BACKGROUND

[0002] In the field of digital image processing and computer vision, when a sensor device (such as a camera) captures an image, the responses of different pixels are often inconsistent due to factors such as hardware manufacturing errors, sensor noise, optical distortion, etc. This inter-pixel inconsistency can cause banding noise, fixed pattern noise (FPN), and result in a decrease in image quality, especially in fine image processing tasks such as high-precision imaging, medical image processing, remote sensing imaging, etc.

[0003] In terms of the specific types of characteristic parameters that differ between pixels in a photosensitive detector imaging chip, non-uniformity is usually manifested in the following two ways: DSNU (Dark Signal Nonuniformity), which refers to the inconsistency in the gray scale values obtained by imaging due to the difference in the dark current of each pixel in the absence of light, corresponding to the intercept term in the light response formula; PRNU (Photo Response Nonuniformity), which refers to the inconsistency in the response of each pixel to light under the same light conditions, corresponding to the slope term in the light response formula.

[0004] For the aforementioned fixed pattern noise FPN, it exhibits a fixed spatial pattern in each pixel of the image sensor, such as a fixed position brightness or color deviation. The commonly used methods to correct the FPN caused by this spatial non-uniformity are black field correction and two-point field correction. Black field correction is convenient to operate, as it only requires subtracting a dark field image once, but it can only solve the problem of inconsistency in the initial gray scale values between pixels; two-point field correction determines the gain and offset of each pixel through two reference images, and then corrects the gain and offset of each pixel. This method can correct both DSNU and PRNU, but the light response curve of the photosensitive detector is not a very strict linear curve, and it cannot handle the non-linear situation when the well is almost full.

[0005] Chinese invention patent CN102938409A proposes a composite medium grid photosensitive detector. The detector has the characteristics that a single semiconductor device can realize complete reset, photosensitive detection, and readout functions, and constitutes a complete pixel, which can greatly improve the fill factor of the pixel. This composite medium grid photosensitive detector has more full-well charges due to the existence of two photoelectron storage nodes in its structure, and existing non-uniformity correction methods cannot handle the non-linear situation when the well is almost full. Therefore, the inconsistency between pixels in this detector will cause more obvious problems. SUMMARY

[0006] In order to solve the existing problems, the application provides a composite correction method for spatial non-uniformity between pixels of a composite medium grid photosensitive detector, comprising:

[0007] Step S1, a segmented fitting method is used to fit the light response curve model of each pixel;

[0008] Step S2, according to the light response curve model data, a multi-point uniform field correction method is used to correct the data collected by the pixel array composed of the composite medium grid photosensitive detector;

[0009] Step S3, it is judged whether the fixed pattern noise corresponding to the data corrected by the multi-point uniform field correction method exceeds the preset DN threshold value;

[0010] Step S4, if the fixed pattern noise corresponding to the corrected data still exceeds the preset DN threshold value, a single-point uniform field correction method is further used for correction.

[0011] Optionally, the step S1 is to use a three-segment fitting method to fit the light response curve model of each pixel, comprising:

[0012] Step S1.1, set the integration time, use uniform light to irradiate the surface of each detector, control the light intensity to gradually increase from 0 to a value just making the detector full well, and collect M pictures at each light intensity point;

[0013] Step S1.2, based on the pictures collected in step S1.1, generate average data for each light intensity point;

[0014] Step S1.3, the data corresponding to the light intensity of 0 is taken as the dark field data, and the pure light response data is generated by subtracting the dark field data from the data of other light intensity points;

[0015] Step S1.4, based on the pure light response data, the three-segment fitting light response curve is performed to determine the slope and intercept of each segment, and then the first fitting light response curve is obtained according to the slope and intercept of each segment.

[0016] Optionally, the basic linear light response curve formula is used when the three-segment fitting light response curve is performed in step S1.4.

[0017]

[0018] Wherein, m1, m2, m3 are the slopes of the three segments respectively, b1, b2, b3 are the intercepts of the three segments respectively, photon1, photon2 are the horizontal coordinates of the intersection points between the three segments; Photon represents the light intensity value, and DN represents the pixel value.

[0019] Optionally, when performing the three-stage fitting of the light response curve in step S1.4, the fitting is performed for each pixel according to the following conditions:

[0020] make Minimum

[0021] make Minimum

[0022] make Minimum

[0023] Among them, DN i Indicates the pixel value corresponding to the i-th light intensity, Photon i Represents the i-th light intensity value.

[0024] Optionally, step S2 corrects the data collected by the pixel array composed of the composite dielectric grating photosensitive detector using a multi-point mean field correction method based on the light response curve model data, including:

[0025] Step S2.1, obtaining the image data to be corrected collected by the pixel array composed of the composite dielectric grating photosensitive detector, and subtracting the dark field image data taken with the same integration time to obtain the pure light response data;

[0026] Step S2.2: Determine the position of each pixel on the light response curve after the first fitting, and perform correction based on its position. The corrected DN value is recorded as DN correct , calculated as follows:

[0027]

[0028] DN correct =K*Photon

[0029] Among them, DN data is the DN value of any pixel, the slope corresponding to the position of any pixel on the light response curve after a fitting is recorded as m, and the intercept is recorded as b; m is any value among m1, m2, and m3, and b is any value among b1, b2, and b3; mean data_DN is the mean DN value of the image to be corrected, mean Photon The DN value of each pixel in the image to be corrected is converted into the average value of the Photon value through the light response curve.

[0030] Optionally, step S4 includes:

[0031] If the fixed pattern noise corresponding to the corrected data still exceeds the preset DN threshold, then find the DN value point closest to it on the light response curve after a fitting, and take it as the DN value.model , the corrected DN value DN correct The specific calculation is as follows:

[0032] DN correct = mean model - (DN model - DN data )

[0033] Wherein, mean model represents the mean of the DN value of the image of the selected DN value point.

[0034] Optionally, the preset DN threshold is an empirical value.

[0035] The present application has the following advantages:

[0036] The present application is aimed at a pixel array composed of a composite medium grid photosensitive detector, and a composite correction method is designed to solve the problem of spatial non-uniformity. According to the characteristics, the light response curve model of each pixel is fitted by segmentation, and according to the light response curve model data, the data collected by the pixel array composed of the composite medium grid photosensitive detector is corrected by using the multi-point field correction method, and the single-point correction method is used for abnormal conditions. This scheme not only can correct the DRNU well, but also can correct the PRNU well, and can solve the problem of micro-light imaging and non-linearity near full well in the light response curve of the composite medium grid photosensitive detector, and further, according to the cache ability of the detector itself, the number of fitted segments and whether to discard abnormal conditions can be reduced or increased. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0038] Figure 1 The composite correction method flow chart for spatial non-uniformity between pixels provided in the present application.

[0039] Figure 2 is a structural schematic diagram of the composite medium grid photosensitive detector in the embodiment.

[0040] Figure 3 is an actual light response curve diagram of the composite medium grid photosensitive detector.

[0041] Figure 4 is the relationship between FPN and the mean of image DN value after using the multi-point field method to process the results of shooting under different light intensities (uniform light).

[0042] Figure 5 is the relationship between FPN and the average of image DN value after using the composite method to post-process the results of shooting under different light intensities (uniform light).

[0043] Figure 6 is an image comparison chart before and after using the composite correction method and the black field correction method to correct spatial non-uniformity, wherein the left image is after correction by the composite correction method, and the right image is after correction by the black field correction method.

[0044] Figure 7 is an image comparison chart when correcting certain abnormal DN value intervals using the composite correction method and the two-point uniform field correction method, wherein the left image is after correction by the composite correction method, and the right image is after correction by the two-point uniform field correction method. DETAILED DESCRIPTION

[0045] To make the objectives, technical solutions and advantages of the present application clearer, the following will further describe the embodiments of the present application in combination with the drawings.

[0046] Embodiment One:

[0047] This embodiment provides a composite correction method for spatial non-uniformity between pixels, as shown in Figure 1 The method is applied to a pixel array composed of composite medium grid photosensitive detectors, and includes:

[0048] Step S1, fitting a light response curve model of each pixel by using piecewise fitting;

[0049] Step S2, correcting data collected by the pixel array composed of composite medium grid photosensitive detectors by using a multi-point uniform field correction method according to the light response curve model data;

[0050] Step S3, judging whether the fixed pattern noise corresponding to the corrected data by using the multi-point uniform field correction method exceeds a preset DN threshold value;

[0051] Step S4, if the fixed pattern noise corresponding to the corrected data still exceeds the preset DN threshold value, further correcting by using a single-point uniform field correction method.

[0052] The method is based on a stable uniform light source generator, and this light source generator is used for lighting when collecting model data.

[0053] The composite medium grid photosensitive detector composing the pixel array is a composite medium grid MOSFET photosensitive detector disclosed in the PCT patent application with publication number WO2010 / 094233A1, as shown in Figure 2As shown, the composite dielectric gate photosensitive detector includes a MOS-C part and a MOSFET part, which are formed on the same P-type semiconductor substrate. The MOS-C part includes a first layer of dielectric layer, a charge-coupled layer, a second layer of dielectric layer and a first control gate which are sequentially stacked on the P-type semiconductor substrate; the MOSFET part includes a first layer of dielectric layer, a charge-coupled layer, a second layer of dielectric layer and a second control gate which are sequentially stacked on the P-type semiconductor substrate, and an N-type source region and an N-type drain region are arranged in the P-type semiconductor substrate and close to one side of the bottom layer of dielectric layer, and a threshold adjustment injection region is arranged in the P-type semiconductor substrate and below the bottom layer of dielectric layer.

[0054] The composite correction method for the spatial non-uniformity between the above-mentioned composite dielectric gate photosensitive detector pixels specifically includes:

[0055] Firstly, a uniform light source is used to irradiate a uniform light on the surface of the detector, and a suitable integration time is set, the light intensity of the uniform light source is changed from no light to the light intensity which just makes the detector full well, and 10 pictures are collected at each light intensity point.

[0056] In the case of no light, i.e. the light intensity is 0, it is assumed that the light intensity from 0 to the light intensity which just makes the detector full well contains n kinds of light intensity, and 10N pictures are collected correspondingly. The integration time can be set according to experience, such as 30 ms or 40 ms.

[0057] Secondly, based on the picture data collected in the first step, the average post-data of each light intensity point is generated.

[0058] For each pixel, the average of the corresponding pixel values of 10 pictures at the same light intensity is taken as the average post-data of the light intensity point.

[0059] Thirdly, the data of no light shooting is taken as the dark field, and the data of each light intensity point is subtracted from the dark field to generate pure light response data.

[0060] Fourthly, the three-section fitting light response curve is carried out based on the pure light response data to determine the slope and intercept of each section.

[0061] As shown in the figure, the light response curve of the composite dielectric gate photosensitive detector presents a three-section feature, and the three-section fitting light response curve has the form of: Figure 3

[0062]

[0063] Wherein, m1, m2 and m3 are the slopes of the three sections respectively, b1, b2 and b3 are the intercepts of the three sections respectively, and photon1 and photon2 are the horizontal coordinates of the intersection points between the three sections.

[0064] ​When performing three-stage fitting of the light response curve, fitting is performed according to the following conditions, taking a single pixel as an example:

[0065] make minimum

[0066] make minimum

[0067] make minimum

[0068] DNi = m1 * Photoni + b1 i DNi = m2 * Photoni + b2 i DNi = m3 * Photoni + b3

[0069] The slope (m1, m2, m3) and intercept (b1, b2, b3) of each segment of the first-order curve are stored, and the light response curve after first-order fitting is obtained according to the slope and intercept of each segment of the curve;

[0070] In the fifth step, the light response curve model of each pixel is restored based on the slope (m1, m2, m3) and intercept (b1, b2, b3) of each segment of the first-order curve determined in the fourth step, and a multi-point field correction method is used:

[0071] In the sixth step, the picture to be corrected is collected, and the DN value of any pixel is taken as an example, which is DN data , and the corresponding first-order fitted light response curve is found, the slope is m, and the intercept is b. The mean value of the DN values of the pixels in the picture to be corrected on the first-order fitted light response curve is mean data_DN , and the mean value of the Photon values converted from the DN values of the pixels in the picture to be corrected through the light response curve is mean photon , then the corrected DN value DN correct is DN

[0072]

[0073] DN correct = K * Photon

[0074] where K is the conversion coefficient from Photon to DN, and Photon is the light intensity value corresponding to the pixel according to the light response curve.

[0075] In the seventh step, the results under different light intensities are processed according to the method of the sixth step, and the abnormal points are found. The abnormal points are the pixel points whose fixed pattern noise is still greater than the number of electrons represented by 1 DN value after the above correction. The number of electrons represented by 1 DN value is determined according to the specific device, such as 40 electrons, and the likeFigure 4 as shown.

[0076] Eighth step, using single-point uniform field method at these abnormal points:

[0077] According to the pure light response data generated in the third step, for any pixel in the collected picture to be corrected, its DN value is DN data , the DN value point closest to it in the model data can be found, which is DN model , and the corrected DN value DN correct is calculated as follows

[0078] DN correct = mean model -(DN model -DN data )

[0079] Wherein, mean model represents the mean of the DN values of the image of the selected DN value point.

[0080] The results of the composite correction method are shown in Figure 5 .

[0081] Finally, the results of the composite correction method and the dark field correction method proposed in the present application are compared, as shown in Figure 6 , it can be seen that the fixed pattern noise processed by the dark field correction method is larger, which is due to the fact that it does not correct the inconsistency of the slope of the light response and in some abnormal DN value intervals; the results of the multi-point uniform field method and the single-point uniform field method are compared, as shown in Figure 7 , it can be seen that the results processed by the single-point uniform field method in the abnormal DN value interval have a lot of abrupt noise, which is also the fixed pattern noise that is not corrected normally.

[0082] Some steps in the embodiments of the present application can be implemented by software, and the corresponding software program can be stored in a readable storage medium, such as an optical disc or a hard disk, etc.

[0083] The above only describes the preferred embodiments of the present application, and is not intended to limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method of composite correction for spatial non-uniformity between pixels, characterized by, The method is applied to a pixel array composed of a composite dielectric grating photosensitive detector, and the method comprises: Step S1, fitting the light response curve model of each pixel using a piecewise fitting method; Step S2, correcting the data collected by the pixel array composed of the composite dielectric grating photosensitive detector using a multi-point mean field correction method based on the light response curve model data; Step S3, determining whether the fixed pattern noise corresponding to the data corrected by the multi-point average field correction method exceeds a preset DN threshold; Step S4: If the fixed pattern noise corresponding to the corrected data still exceeds the preset DN threshold, further correction is performed using a single-point mean field correction method; The step S2 corrects the data collected by the pixel array composed of the composite dielectric grating photosensitive detector using a multi-point mean field correction method based on the light response curve model data, including: Step S2.1, obtaining the image data to be corrected collected by the pixel array composed of the composite dielectric grating photosensitive detector, and subtracting the dark field image data taken with the same integration time to obtain the pure light response data; Step S2.2, determine the position of each pixel on the light response curve after one fitting, correct it according to its position, and the corrected DN value is denoted as DN correct The calculation method is as follows: DN correct = K * Photon DN data is the DN value of any pixel, the slope of the position corresponding to any pixel on the light response curve after one fitting is recorded as m, and the intercept is recorded as b; mean data_DN is the mean value of the DN value of the picture to be corrected, mean Photon is the mean value of the DN value of each pixel in the picture to be corrected converted into Photon value through the light response curve; The step S4 comprises: If the fixed pattern noise corresponding to the corrected data still exceeds the preset DN threshold, the DN value point closest to the DN value is found in the model data, and the DN value is taken as the DN model value DN correct The specific calculation is as follows: DN correct = mean model -(DN model -DN data ) wherein, mean model DN value mean of the image representing the selected DN value point.

2. The method of claim 1, wherein, The step S1 is to fit the light response curve model of each pixel using a three-segment fitting method, including: Step S1.1: Set the integration time, illuminate the surface of each detector with uniform light, and gradually increase the light intensity from 0 to a value that just fills the detector well. Collect M images at each light intensity point. Step S1.2, generating average data for each light intensity point based on the image collected in step S1.1; Step S1.3, taking the data corresponding to the light intensity of 0 as the dark field data, and subtracting the dark field data from the data of other light intensity points to generate the pure light response data; Step S1.4, performing a three-segment fitting of the light response curve based on the pure light response data, determining the slope and intercept of each segment, and then obtaining a light response curve after a single fitting based on the slope and intercept of each segment curve.

3. The method of claim 2, wherein, When performing the three-stage fitting of the light response curve in step S1.4, the basic linear light response curve formula is: Among them, m1, m2, and m3 are the slopes of the three segments, b1, b2, and b3 are the intercepts of the three segments, photon1 and photon2 are the horizontal coordinates of the intersections of the three segments; Photon represents the light intensity value, and DN represents the pixel value.

4. The method of claim 3, wherein, When performing the three-stage fitting of the light response curve in step S1.4, the fitting is performed for each pixel according to the following conditions: making minimum making minimum making minimum where DN i represents the pixel value corresponding to the i-th light intensity, Photon i represents the i-th light intensity value.

5. The method of claim 4, wherein, The preset DN threshold is an empirical value.

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