Non-uniform background suppression method for wide-area star map of CCD (Charge Coupled Device) sensor

Abstract

The invention discloses a CCD sensor wide-area star map non-uniformity background suppression method, which comprises the following steps of: firstly, describing the form of an image, analyzing background imaging characteristics in the image by utilizing description information, and then carrying out integral non-uniformity background estimation and background suppression on a star sky image by adopting fixed window one-dimensional median filtering. And then based on a local contrast thought, adaptive one-dimensional median filtering is adopted to carry out accurate estimation and background suppression on the processed starry sky image. According to the method, noise, heterogeneity and bright lines caused by Smear in the star map background can be effectively removed at the same time, and fixed stars and targets on the star map are stored while the background is suppressed.

Description

Technical Field

[0001] The invention belongs to the technical field of computer vision, and in particular relates to a method for suppressing non-uniform background of a wide-area star image of a CCD sensor. Background Art

[0002] Background suppression technology is a method used to reduce or eliminate background interference in images. It is widely used in the fields of image processing and computer vision, especially in target detection and tracking tasks. In the process of space target imaging, due to the influence of stray light in space and the detection equipment itself, a large amount of noise appears in the image, which reduces the imaging quality of the image and affects the accuracy of target detection and the accuracy of target centroid positioning. Therefore, it is necessary to preprocess the image to improve the image quality and reduce the impact of noise on target detection and positioning. The classic denoising methods mainly include image frequency domain filtering, mean filtering, median filtering, Gaussian filtering, Wiener filtering, wavelet transform, etc.

[0003] CCD image sensors can directly convert optical signals into digital electrical signals, have low power consumption, stable performance, low noise, and high pixel integration, and are widely used in space target observation and reconnaissance, space debris warning, astronomical observation and other fields. The research on wide-area star map background suppression is mainly to provide guarantee for space target extraction. By processing the image before target detection, the purpose of suppressing or eliminating background non-uniform noise is achieved. In the star map, the imaging size, shape, and grayscale value of the space target are highly similar to the noise. The image background is unevenly distributed under the influence of stray light. For CCD detectors, bright lines caused by the Smear effect will appear in the image. The above factors make it difficult to apply traditional image denoising algorithms to the denoising process of star maps.

[0004] In recent years, based on the research results of star image background suppression at home and abroad, the processing of star image background suppression is roughly the following steps:

[0005] 1) Data preprocessing: Preprocess the image, including denoising, smoothing and grayscale operations, to improve the effect of subsequent processing;

[0006] 2) Background segmentation: Segment the image into target area and background area. Common techniques include threshold segmentation, edge detection and other methods.

[0007] 3) Background estimation: By performing background estimation, the background signal in the star map is identified and quantified, usually by using methods such as mean filtering and smoothing filtering;

[0008] 4) Background suppression: Subtract the established background model from the original star map data to suppress the background signal. This can be achieved by pixel-by-pixel subtraction or other mathematical calculations.

[0009] In the step of background suppression of star images, the quality of background estimation determines the quality of background suppression effect. Through reasonable and accurate modeling and estimation, the system can more effectively identify foreground targets in the image, thereby achieving accurate background suppression. Choosing a suitable background estimation method is crucial to the success of the entire background suppression process. The commonly used background estimation technology is "background estimation based on statistical methods". Background estimation based on statistical methods usually draws a histogram of pixel brightness and then analyzes this distribution to determine the statistical parameters of the background. Background estimation is achieved by setting a threshold. Because celestial bodies and other bright spots are high-brightness outliers in the image, statistical analysis focuses on dark pixels in the image, that is, only pixels below a certain brightness value are counted in the background estimation. For star images under non-uniform illumination conditions, the accuracy of background estimation based on statistical methods will be greatly affected. At the same time, when removing the estimated background, the signals of dim targets may also be mistakenly removed, especially those targets with brightness close to the background level. In order to solve the problem of low background estimation accuracy and easy misremoval of dim targets under non-uniform illumination conditions, this project proposes a CCD sensor wide-area star image non-uniform background suppression method to achieve the purpose of background suppression. Background suppression is of great significance for the extraction of space dim targets. Summary of the invention

[0010] In order to overcome the shortcomings of the prior art, the present invention provides a CCD sensor wide-area star map non-uniform background suppression method, firstly, the form of the image is described, the background imaging characteristics in the image are analyzed using the description information, and then the fixed window one-dimensional median filter is used to estimate the overall non-uniform background of the starry sky image and suppress the background, and then based on the local contrast idea, the processed starry sky image is accurately estimated and the background is suppressed using an adaptive one-dimensional median filter. The method of the present invention can effectively remove the noise, non-uniformity and bright lines caused by smear in the star map background, and preserve the stars and targets on the star map while suppressing the background.

[0011] The technical solution adopted by the present invention to solve the technical problem is as follows:

[0012] Step 1: Analyze the imaging characteristics of the starry sky observation image and describe the starry sky observation image as:

[0013] I(x,y)=I s (x,y)+I B (x,y)+I N (x,y)+I L (x,y)

[0014] Where I(x, y) is the observation image obtained by the CCD focal plane of the observation camera; (x, y) is the coordinate of the pixel point, and 1≤x≤M, 1≤y≤N, where M=4096, N=4096; I S (x, y) is the target image, including the observation images of stars and space targets; I B (x, y) is the starry sky background image; I N (x, y) is a noise image, including spatial radiation noise, CCD fixed noise, and dark background noise, and it is assumed that I N (x,y) is subject to zero-mean Gaussian noise; I L (x,y) is the Smear image;

[0015] A one-dimensional median filter is performed on the original image using a window of size W0 to estimate the overall non-uniform background. The background estimate B0 is:

[0016]

[0017] By performing a difference with the original image, the image I0 obtained by removing the overall non-uniform noise in the background and the bright lines on the image caused by the Smear effect is:

[0018] I0(x,y)=I(x,y)-B0(x,y)

[0019] Where I0(x, y) is the gray value at the (x, y) coordinate position in image I0, and image I0 is the image obtained after the non-uniform background of the wide-area star map CCD sensor is initially suppressed;

[0020] Step 2: Count the grayscale value and T of each pixel of image I0, and calculate T according to the following formula:

[0021]

[0022] Where (x, y) is the coordinate of the pixel, I0(x+i, y+j) is the gray value at the coordinate position (x+i, y+j) in image I0, and a is the local contrast value;

[0023] The local contrast T is calculated according to the following formula l :

[0024]

[0025] Local contrast T l Used to adaptively adjust the size of the variable window;

[0026] Step 3: Use the variable window size method to perform one-dimensional median filtering on image I0 to estimate the non-uniform background; according to the local contrast T obtained in step 2 l, determine the size of the filter window W1, the threshold T t Determined by the following formula:

[0027]

[0028] In the formula, μ B is the grayscale mean of the statistical image I0;

[0029] The non-uniform background estimation B1 of image I0 obtained by adaptive filtering is:

[0030]

[0031] Differentiate with image I0 to remove the non-uniform background, and get image I1 as:

[0032] I1(x,y)=I0(x,y)-B1(x,y)

[0033] Image I1 is the image obtained after the non-uniform background of the wide-area star image of the final CCD sensor is suppressed.

[0034] Furthermore, the one-dimensional median filter processing window W0 in step 1 is 128.

[0035] Furthermore, the local comparison range a in step 2 is 24.

[0036] Furthermore, in step 3, according to the local contrast T l With threshold T t The size of the filter window W1 is adjusted according to the size relationship. W1 represents the one-dimensional median filter window being processed with the center at (x, y). st The default initial window size for W1, W max is the maximum window size allowed by W1; its adjustment steps are:

[0037] Step 3-1: Initial window W1 = W st , if the current one-dimensional median filter window centered at (x, y) is T l <T t , then the output window size is W st The filtering result is obtained when the filter is processed, otherwise go to step 3-2;

[0038] Step 3-2: If W1 <W max , then increase the window: W1 plus C0, go to step 3-1, otherwise go to step 3-3;

[0039] Step 3-3: At this time, W1 = W max , then the output window size is W max The filtering result at .

[0040] Furthermore, the initial window size W st is 24, W max is 48, and the constant C0 is 8.

[0041] The beneficial effects of the present invention are as follows:

[0042] The method of the present invention can effectively remove noise, non-uniformity and bright lines caused by smear in the background of the star map at the same time, and preserve the stars and targets on the star map while suppressing the background. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a diagram for implementing the framework of the method for suppressing the non-uniform background of a wide-area star image of a CCD sensor according to an embodiment of the present invention.

[0044] Figure 2 This is a one-dimensional median filtering principle diagram of an embodiment of the present invention.

[0045] Figure 3 This is a wide-area starry sky observation image of the CCD sensor used in the embodiment of the present invention.

[0046] Figure 4 For the general Figure 3 The image is obtained after background suppression according to the method of the present invention. DETAILED DESCRIPTION

[0047] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0048] In order to overcome the deficiency of existing star image background suppression algorithms that remove some stars and dim targets on the image while suppressing the background, the present invention proposes a CCD sensor wide-area star image non-uniform background suppression method. This method can effectively remove noise, non-uniformity and bright lines caused by smear in the star image background at the same time. The estimation of non-uniform noise background is more accurate than traditional algorithms and does not require image prior information.

[0049] A method for suppressing non-uniform background of wide-area star images of a CCD sensor comprises the following steps:

[0050] ① Analyze the imaging characteristics of the starry sky observation image and describe the starry sky observation image as:

[0051] I(x,y)=I s (x,y)+I B (x,y)+I N (x,y)+I L (x,y)

[0052] Where I(x, y) is the observation image obtained by the CCD focal plane of the observation camera; (x, y) is the coordinate of the pixel point, and 1≤x≤M, 1≤y≤N, where M=4096, N=4096; I S (x, y) is the target image, including the observation images of stars and space targets; I B (x, y) is the starry sky background image; I N (x, y) is a noise image, including spatial radiation noise, CCD fixed noise, dark background noise, and is assumed to obey zero-mean Gaussian noise; I L (x,y) is the Smear image;

[0053] A one-dimensional median filter is performed on the original image using a window of size W0 to estimate the overall non-uniform background. The background estimate B0 is:

[0054]

[0055] By subtracting the original image, we can get the image I0 without the overall non-uniform noise in the background and the bright lines on the image caused by the Smear effect.

[0056] I0(x,y)=I(x,y)-B0(x,y)

[0057] Image I0 is the image obtained after the initial suppression of the non-uniform background of the wide-area star map CCD sensor;

[0058] ② Count the grayscale value and T of each pixel of image I0, and calculate T according to the following formula:

[0059]

[0060] Where (x, y) is the coordinate of the pixel, I0(x+i, y+j) is the gray value at the coordinate position (x+i, y+j) in image I0, and a is the local contrast value;

[0061] The local contrast T is calculated according to the following formula l :

[0062]

[0063] Where I0(x, y) is the gray value at the (x, y) coordinate position in image I0, and the local contrast T l Used to adaptively adjust the size of the variable window;

[0064] ③ Use the variable window size method to perform one-dimensional median filtering on the image obtained in the previous step to accurately estimate the non-uniform background; according to the local contrast T obtained in ② l , determine the size of the filter window W1, the threshold Tt The threshold is determined by the following formula:

[0065]

[0066] Where I0(x,y) is the gray value at the (x,y) coordinate position, μ B is the grayscale mean of the statistical image I0;

[0067] The non-uniform background estimation B1 of image I0 obtained by adaptive filtering is:

[0068]

[0069] Differentiate with image I0 to remove the non-uniform background, and get image I1:

[0070] I1(x,y)=I0(x,y)-B1(x,y)

[0071] Image I1 is the image obtained after the non-uniform background of the wide-area star image of the final CCD sensor is suppressed.

[0072] According to the local contrast T l With threshold T t The size of the filter window W1 is adjusted according to the size relationship. W1 represents the one-dimensional median filter window being processed with the center at (x, y). st The default initial window size for W1, W max is the maximum window size allowed by W1. The adjustment steps are:

[0073] a) Initial window W1 = W st , if the current one-dimensional median filter window centered at (x, y) is T l <T t , then the output window size is W st The filtering result when is, otherwise go to b);

[0074] b) If W1 <W max , then increase the window: W1=W1+C0, go to a), otherwise go to c);

[0075] c) At this time, W1=W max , then the output window size is W max The filtering result at .

[0076] Initial window size W st is 24, W max is 48, and the constant C0 is 8.

[0077] Example:

[0078] Figure 1This is a framework diagram of an implementation of a method for suppressing non-uniform background of a wide-area star image of a CCD sensor in this embodiment, and the specific implementation steps are as follows:

[0079] Step 1: Analyze the imaging characteristics of the input CCD sensor wide-area star map, process the image as a whole, obtain the overall non-uniform background estimation result of the image and suppress it.

[0080] Generally speaking, in the process of imaging space targets, due to the influence of stray light in space and the detection equipment itself, a large amount of noise appears in the image, which reduces the imaging quality of the image and affects the accuracy of target detection and tracking. Therefore, it is necessary to preprocess the image to improve the image quality and reduce the impact of noise on target detection and tracking. The sources of background noise mainly include: space radiation noise, noise of the imaging system detector itself, and dark background noise.

[0081] By analyzing the background imaging characteristics in the image, the star observation image is described as:

[0082] I(x,y)=I s (x,y)+I B (x,y)+I N (x,y)+I L (x,y)

[0083] Where I(x, y) is the observation image obtained by the CCD focal plane of the observation camera; (x, y) is the coordinate of the pixel point, and 1≤x≤M, 1≤y≤N, where M=4096, N=4096; I S (x, y) is the target image, including the observation images of stars and space targets; I B (x, y) is the starry sky background image; I N (x, y) is a noise image, including spatial radiation noise, CCD fixed noise, dark background noise, and is assumed to obey zero-mean Gaussian noise; I L (x,y) is the Smear image.

[0084] According to the background imaging characteristics analysis of the star observation map, the original image column contains targets and stars, so the grayscale values ​​of some pixels are high. At the same time, due to the pollution of non-uniform noise, the grayscale values ​​of each column of pixels in the image fluctuate greatly. Selecting a larger window can estimate the non-uniform fluctuations of the background.

[0085] Therefore, one-dimensional median filtering is used for processing, and its principle is as follows Figure 2 As shown, at this time, the filter window size is W0=128, and the overall non-uniform background estimation is performed, and the background estimation B0 is;

[0086]

[0087] By subtracting the original image, we can get the image I0 without the overall non-uniform noise in the background and the bright lines on the image caused by the Smear effect.

[0088] I0(x,y)=I(x,y)-B0(x,y)

[0089] Image I0 is the image obtained after the non-uniform background of the wide-area star map CCD sensor is initially suppressed.

[0090] Step 2: Count the grayscale value of each pixel of the image I0 obtained in step 1, and then calculate its local contrast to obtain the basis for the adaptive filtering window for estimating the local non-uniform background.

[0091] For star maps, most of the pixels in the image belong to the background and have low grayscale values. The grayscale value distribution range is relatively concentrated. At the same time, there are target and star pixels with higher grayscale values. Some pixels even have saturated grayscale values ​​and their distribution range is relatively dispersed.

[0092] Therefore, the gray value and T of each pixel of image I0 are counted, and T is calculated according to the following formula:

[0093]

[0094] Where (x, y) is the coordinate of the pixel point, I0(x+i, y+J) is the gray value at the coordinate position (x+i, y+j) in image I0, a is the local contrast range, a=24;

[0095] The local contrast T is calculated according to the following formula l :

[0096]

[0097] Where I0(x, y) is the gray value at the (x, y) coordinate position in image I0, and the local contrast T l Used to adaptively adjust the size of the variable window.

[0098] Step 3: Process the image accurately to estimate the local non-uniform background and suppress it.

[0099] Using a larger window can estimate the background non-uniformity fluctuations, but the overall background gray value curve is relatively flat and cannot accurately estimate the local non-uniformity. At the same time, median filtering requires sorting the pixel gray values ​​in the window, and a large window will introduce a large amount of calculation; however, the smaller the window, the better. Although a small window can estimate the local non-uniformity in the background more accurately, if the window contains targets or stars, if the target or star occupies more than 50% of the pixels in the small window, the pixels of the target or star will be mistakenly estimated as the background, resulting in the loss of target information during background subtraction.

[0100] Therefore, a variable window size method is used to perform one-dimensional median filtering on the image obtained in the previous step, and the residual local non-uniform noise in the image is further removed to accurately estimate the non-uniform background. According to the local contrast T obtained in step 2, l , determine the size of the filter window W1, the threshold T t The threshold is determined by the following formula:

[0101]

[0102] Where I0(x,y) is the gray value at the (x,y) coordinate position, μ B is the gray value of the statistical image I0;

[0103] According to the local contrast T l With threshold T t The size of the filter window W1 is adjusted according to the size relationship. W1 represents the one-dimensional median filter window being processed with the center at (x, y). st The default initial window size for W1, W st =24,W max is the maximum window size allowed by W1, W max =48, C0 is a constant, C0=8. The adjustment steps are:

[0104] a) Initial window W1 = W st , if the current one-dimensional median filter window centered at (x, y) is T l <T t , then the output window size is W st The filtering result when is, otherwise go to b);

[0105] b) If W1 <W max , then increase the window: W1=W1+C0, go to a), otherwise go to c);

[0106] c) At this time, W1=W max , then the output window size is W max The filtering result at .

[0107] The non-uniform background estimation B1 of image I0 obtained by adaptive filtering is:

[0108]

[0109] Differentiate with image I0 to remove the non-uniform background, and get image I1:

[0110] I1(x,y)=I0(x,y)-B1(x,y)

[0111] Image I1 is the image obtained after the non-uniform background of the wide-area star image of the final CCD sensor is suppressed.

[0112] Figure 3 The CCD sensor wide-area starry sky observation image used in the embodiment of the present invention, Figure 4 For the general Figure 3 The image shown is the image after background suppression by the above method. It can be seen that the non-uniform background noise of the original image is well removed, and the low signal-to-noise ratio targets in the star map are retained.

Claims

1. A method for suppressing non-uniform background of wide-area star images of a CCD sensor, characterized in that: The steps include: Step 1: Analyze the imaging characteristics of the starry sky observation image and describe the starry sky observation image as: I(x,y)=I s (x,y)+I B (x,y)+I N (x,y)+I L (x,y) Where I(x, y) is the observation image obtained by the CCD focal plane of the observation camera; (x, y) is the coordinate of the pixel point, and 1≤x≤M, 1≤y≤N, where M=4096, N=4096; I S (x, y) is the target image, including the observation images of stars and space targets; I B (x, y) is the starry sky background image; I N (x, y) is a noise image, including spatial radiation noise, CCD fixed noise, and dark background noise, and it is assumed that I N (x,y) is subject to zero-mean Gaussian noise; I L (x,y) is the Smear image; A one-dimensional median filter is performed on the original image using a window of size W0 to estimate the overall non-uniform background. The background estimate B0 is: By performing a difference with the original image, the image I0 obtained by removing the overall non-uniform noise in the background and the bright lines on the image caused by the Smear effect is: I0(x,y)=I(x,y)-B0(x,y) Where I0(x, y) is the gray value at the (x, y) coordinate position in image I0, and image I0 is the image obtained after the non-uniform background of the wide-area star map CCD sensor is initially suppressed; Step 2: Count the grayscale value and T of each pixel of image I0, and calculate T according to the following formula: Where (x, y) is the coordinate of the pixel, I0(x+i, y+j) is the gray value at the coordinate position (x+i, y+j) in image I0, and a is the local contrast value; The local contrast T is calculated according to the following formula l : Local contrast T l Used to adaptively adjust the size of the variable window; Step 3: Use the variable window size method to perform one-dimensional median filtering on image I0 to estimate the non-uniform background; according to the local contrast T obtained in step 2 l , determine the size of the filter window W1, the threshold T t Determined by the following formula: In the formula, μ B is the grayscale mean of the statistical image I0; The non-uniform background estimation B1 of image I0 obtained by adaptive filtering is: Differentiate with image I0 to remove the non-uniform background, and get image I1 as: I1(x,y)=I0(x,y)-B1(x,y) Image I1 is the image obtained after the non-uniform background of the wide-area star image of the final CCD sensor is suppressed.

2. The method for suppressing non-uniform background of wide-area star image of CCD sensor according to claim 1, characterized in that: The one-dimensional median filter processing window W0 in step 1 is 128.

3. The method for suppressing non-uniform background of wide-area star image of CCD sensor according to claim 1, characterized in that: The local comparison range a in step 2 is 24.

4. The method for suppressing non-uniform background of wide-area star image of CCD sensor according to claim 1, characterized in that: In step 3, according to the local contrast T l With threshold T t The size of the filter window W1 is adjusted according to the size relationship. W1 represents the one-dimensional median filter window being processed with the center at (x, y). st The default initial window size for W1, W max The maximum window size allowed for W1; The adjustment steps are: Step 3-1: Initial window W1 = W st , if the current one-dimensional median filter window centered at (x, y) is T l <T t , then the output window size is W st The filtering result is obtained when the filter is processed, otherwise go to step 3-2; Step 3-2: If W1 <W max , then increase the window: W1 plus C0, go to step 3-1, otherwise go to step 3-3; Step 3-3: At this time W1=W max , then the output window size is W max The filtering result at .

5. The method for suppressing non-uniform background of wide-area star image of CCD sensor according to claim 1, characterized in that: The initial window size W st is 24, W max is 48, and the constant C0 is 8.

Images