Infrared detector fixed pattern noise correction method

Abstract

The invention relates to an infrared detector fixed pattern noise correction method, and belongs to the technical field of infrared imaging. According to the method, the fixed pattern noise phenomenon of the infrared detector serves as a template, the fixed pattern noise intensity in the real-time image is obtained through correlation calculation in the real-time image, and the fixed pattern noise of the infrared detector in the real-time image can be eliminated.

Description

Technical Field

[0001] The invention belongs to the technical field of infrared imaging, and in particular relates to a method for correcting fixed pattern noise of an infrared detector. Background Art

[0002] The staring infrared detector is a large-array semiconductor device. Due to the discreteness of the parameters of the device material itself, the complex processing process, and the many steps, the performance parameters of each detection unit of the infrared focal plane array will be different, resulting in the inconsistency of the infrared response between the detection units. This is the non-uniformity of the detector, also known as fixed pattern noise or fixed graphic noise. The fixed pattern is generated during the preparation of the infrared detector component. Each detector has its own fixed pattern noise phenomenon, and the intensity of the noise will vary with different working conditions.

[0003] The non-uniformity of the infrared detector needs to be corrected and the fixed pattern noise eliminated to ensure the normal use of the detector.

[0004] At present, most infrared imaging systems use a blackbody-based calibration method, that is, a blackbody is placed in front of the infrared detector or infrared imager, and the blackbody is used as a uniform radiation source to measure the response of each pixel of the detector, and the correction parameters are obtained based on the response value. This process is called calibration; after the calibration is completed, these data are read and corresponding operations are performed during the working process, and this process is called correction. Specific correction algorithms include single temperature point correction and two temperature point correction, as shown in equations (1) to (4).

[0005] 1) Single temperature point correction algorithm

[0006] Calibration formula:

[0007]

[0008] Correction formula:

[0009] Y ij (T) = X ij (T)+O ij (2)

[0010] 2) Two temperature point correction algorithm

[0011] Calibration formula:

[0012]

[0013] Correction formula:

[0014] Y ij (T) = G ij X ij (T)+O ij (4)

[0015] Where X ij (T) is the response output of pixel (i, j) to a black body with a radiation temperature of T, is the average value of the response output of all pixels to the black body with radiation temperature T, T1 and T2 are the temperatures of the calibrated black body, G ij and O ij is the correction parameter for each pixel, Y ij (T) is the corrected result.

[0016] The non-uniformity correction method based on blackbody calibration uses blackbody as the reference source and has the characteristics of scene dependence. When the radiation characteristics of the scene used are inconsistent with the calibration blackbody, the blackbody calibration method cannot achieve a good correction effect. There are two limitations:

[0017] 1) The radiance of the scene during calibration is equivalent to the radiance of the black body during calibration;

[0018] 2) The spectral distribution of the scene during correction is equivalent to the spectral distribution of blackbody radiation during calibration.

[0019] Therefore, when the use environment is inconsistent with the calibration environment, the detector fixed pattern will degrade. Summary of the invention

[0020] 1. Technical issues to be resolved

[0021] The technical problem to be solved by the present invention is to design a detector fixed pattern correction method which is not dependent on the environment.

[0022] (II) Technical solution

[0023] In order to solve the above technical problems, the present invention provides a method for correcting fixed pattern noise of an infrared detector, comprising the following steps:

[0024] 1) Step 1, calibration:

[0025] The infrared detector output image that has not been corrected for non-uniformity is processed by median filtering to obtain an image with a clean background and only retaining the fixed pattern noise phenomenon of the infrared detector, which is used as the template image Z0(x,y);

[0026] 2) Step 2, calculate the correlation:

[0027] Through the correlation operation between the real-time image generated by the infrared detector and the template image Z0(x,y), the characteristic parameters are extracted from the image, and the correlation coefficient between the real-time image and the template image is obtained as the correction coefficient;

[0028] Assume that the real-time image generated by the infrared detector when working is I(x,y), and calculate the correlation coefficient between the real-time image and the template image according to the following formula:

[0029] Autocorrelation coefficient:

[0030] Mutual correlation coefficient:

[0031] Correlation coefficient: α = r2 / r1;

[0032] Where I is the infrared image in the current state, It is the grayscale average value of all pixels in the infrared image; is the grayscale average of all pixels in the template;

[0033] 3) Step 3, calibration:

[0034] In the real-time image, the product of the template image and the correlation coefficient is subtracted to obtain the corrected infrared image: I = I-α×Z0.

[0035] The present invention also provides a system for implementing the method.

[0036] The invention also provides an application of the method in the field of infrared imaging technology.

[0037] The invention also provides an application of the system in the field of infrared imaging technology.

[0038] (III) Beneficial effects

[0039] The effect of the present invention is that for a general infrared imaging system, the present invention can eliminate the fixed pattern noise of the infrared detector in the real-time image by taking the fixed pattern noise phenomenon of the infrared detector as a template and obtaining the fixed pattern noise intensity in the real-time image through correlation calculation in the real-time image. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 This is a schematic diagram of the infrared imaging system;

[0041] Figure 2 This is a schematic diagram of the infrared imaging system workflow;

[0042] Figure 3 is the infrared fixed pattern noise template;

[0043] Figure 4 is the infrared detector pattern noise degraded image;

[0044] Figure 5 This is an image after the fixed pattern noise correction of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, content and advantages of the present invention more clear, the specific implementation methods of the present invention are further described in detail below in conjunction with the drawings and examples.

[0046] The invention provides a correction method for fixed pattern noise of an infrared detector, and in particular relates to a correction method based on image similarity calibration.

[0047] The general infrared imaging system includes optical system, infrared detector assembly, image preprocessing circuit and other components, such as Figure 1 The radiation of the scene passes through the focusing lens of the optical system to the focal plane of the infrared detector. The infrared detector converts the scene information into an electrical signal, which is read out by the back-end information processing, processed and displayed to obtain the image of the scene.

[0048] In the present invention, for an infrared detector or an imaging device with an infrared detector as the core, after non-uniformity correction, the fixed pattern noise of the infrared detector appears in the output image of the infrared detector stimulated by changes in the environment, and the image is stored as a template; or in the original image that has not been corrected for non-uniformity, an image with a clean background and only retaining the fixed pattern noise phenomenon of the detector is made through filtering and other methods as a template. The above template is called a fixed noise image template, or simply template. In use, the infrared image and the template are correlated in real time to obtain a correlation coefficient, and the template is multiplied by the correlation coefficient as real-time fixed pattern noise, which is subtracted from the real-time image to obtain a corrected image.

[0049] The infrared detector fixed pattern noise correction method of the present invention is further described below:

[0050] 1) Step 1, calibration:

[0051] The infrared detector output image that has not been corrected for non-uniformity is processed by median filtering to obtain an image with a clean background and only retaining the fixed pattern noise phenomenon of the infrared detector. This image is used as the template image Z0 (x, y) and stored in the memory of the infrared imaging system.

[0052] 2) Step 2, calculate the correlation:

[0053] By performing a correlation operation between the real-time image generated by the infrared detector and the template image Z0 (x, y), characteristic parameters are extracted from the image, and a correlation coefficient (correlation coefficient) between the real-time image and the template image is obtained as a correction coefficient.

[0054] Assume that the real-time image generated by the infrared detector when working is I(x,y), and calculate the correlation coefficient between the real-time image and the template image according to the following formula:

[0055] Autocorrelation coefficient:

[0056] Mutual correlation coefficient:

[0057] Correlation coefficient: α=r2 / r1.

[0058] Where I is the infrared image in the current state, It is the grayscale average value of all pixels in the infrared image; is the average grayscale value of all pixels in the template.

[0059] 3) Step 3, calibration:

[0060] In the real-time image, the product of the template image and the correlation coefficient is subtracted to obtain the corrected infrared image.

[0061] Image correction: I = I-α×Z0

[0062] Figure 3 It is a fixed pattern noise template of infrared detector made using the original image without non-uniformity correction; Figure 4 It is a fixed pattern degradation phenomenon that occurs during the use of an infrared imaging system that has been corrected for non-uniformity; Figure 5 It is the infrared image corrected by the method. It can be seen that for the infrared imaging system, the present invention can eliminate the fixed pattern noise of the infrared detector in the real-time image.

[0063] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for correcting fixed pattern noise of infrared detectors, It is characterized in that The following steps are involved: 1) Step 1, calibration: The infrared detector output image that has not been corrected for non-uniformity is processed by median filtering to obtain an image with a clean background and only the fixed pattern noise of the infrared detector, which is used as the template image Z 0 (x,y); 2) Step 2, calculate the correlation: The real-time image generated by the infrared detector and the template image Z 0 (x, y) correlation operation, extracting feature parameters from the image, and obtaining the correlation coefficient between the real-time image and the template image as the correction coefficient; Assume that the real-time image generated by the infrared detector when working is I(x,y), and calculate the correlation coefficient between the real-time image and the template image according to the following formula: Autocorrelation coefficient: Mutual correlation coefficient: Correlation coefficient: α = r 2 r 1 ; Where I is the infrared image in the current state, It is the grayscale average value of all pixels in the infrared image; is the grayscale average of all pixels in the template; 3) Step 3, calibration: In the real-time image, the product of the template image and the correlation coefficient is subtracted to obtain the corrected infrared image: I = I-α×Z 0 .

2. The method according to claim 1, It is characterized in that In step 1, the template image Z 0 (x, y) is stored in the memory of the infrared imaging system.

3. The method according to claim 2, It is characterized in that In the infrared imaging system, the radiation of the scene passes through the converging lens of the optical system to the focal plane of the infrared detector. The infrared detector converts the scene information into electrical signals, which are read out by the back-end information processing, processed and displayed to obtain the image of the scene.

4. The method according to claim 2, It is characterized in that The infrared imaging system also includes a power supply circuit.

5. The method according to claim 2, It is characterized in that The infrared imaging system also includes an analog-to-digital conversion circuit.

6. The method according to claim 1, It is characterized in that The infrared detector is a staring infrared detector.

7. The method according to claim 6, It is characterized in that The staring infrared detector is a large-array semiconductor device.

8. A system for implementing the method according to any one of claims 1 to 7.

9. Application of the method according to any one of claims 1 to 7 in the field of infrared imaging technology.

10. Application of the system as claimed in claim 9 in the field of infrared imaging technology.

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