A non-uniform correction method of continuous adjustable integration time in wide temperature range

Abstract

This application provides a non-uniform correction method with continuously adjustable integration time over a wide temperature range, including establishing an independent variable T. b t int The function value is Y ij The radiometric calibration model has radiometric calibration coefficients; the radiometric calibration coefficients are solved; the mean radiometric calibration coefficients are solved based on the solved radiometric calibration coefficients, thereby obtaining the mean radiometric calibration model; the images captured by the infrared detector are corrected based on the radiometric calibration model and the mean radiometric calibration model; this application can correct non-uniform images captured by the infrared detector by establishing radiometric calibration equations and mean radiometric calibration equations.

Description

Technical Field

[0001] This application relates to the field of non-contact sensing technology, and in particular to a non-uniform correction method with continuously adjustable integration time over a wide temperature range. Background Technology

[0002] Current non-uniformity correction methods mainly include calibration-based correction algorithms and scene-based correction algorithms. Scene-based correction algorithms suffer from real-time convergence issues, which are not conducive to rapid adjustment of integration time. Calibration-based correction algorithms are mainly divided into temperature model-based methods and integration time model-based methods. Among temperature model-based correction methods, the multi-segment two-point correction method is currently widely used in engineering, with advantages such as simple operation and high reliability. The classic multi-segment two-point correction method generally requires pre-calibration and storage of a limited number of correction parameters corresponding to different integration times. In actual use, the correction coefficient table is called according to the scene temperature conditions. This method has good engineering applications in ground equipment and subsonic aircraft equipment. However, the aerodynamic thermal effect of supersonic flight platforms causes a sudden change in the temperature of the infrared radome. Existing infrared imaging systems mostly use multi-segment two-point non-uniformity correction methods to correct infrared detectors, but the images captured by this correction method still have non-uniformity problems.

[0003] Therefore, this application provides a non-uniform correction method with continuously adjustable integral time over a wide temperature range to solve the above problems. Summary of the Invention

[0004] The purpose of this application is to provide a non-uniform correction method with continuously adjustable integral time over a wide temperature range to address the above problems.

[0005] This application provides a non-uniform correction method with continuously adjustable integration time over a wide temperature range, including:

[0006] Let the independent variable be T b t int The function value is Y ij A radiation calibration model, wherein the radiation calibration model has a set of radiation calibration coefficients;

[0007] The radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel of the infrared detector are solved to obtain multiple sets of radiometric calibration coefficients;

[0008] A set of average radiometric calibration coefficients is obtained by solving multiple sets of radiometric calibration coefficients. The average radiometric calibration coefficients are then substituted into the radiometric calibration model to obtain the average radiometric calibration model.

[0009] The images captured by the infrared detector are corrected based on the radiometric calibration model and the average radiometric calibration model.

[0010] According to the technical solution provided in the embodiments of this application, the radiation calibration model is as follows:

[0011]

[0012] Where: Y ij This represents the grayscale value of a pixel.

[0013] a ij b ij c ij d ij e ij f ij These are correction factors; six correction factors form a set of radiation calibration factors.

[0014] t int The integration time;

[0015] T b The temperature value of the pixel;

[0016] i is the row number of the pixel, which is a natural number greater than 0;

[0017] j is the column number of the pixel, which is a natural number greater than 0.

[0018] According to the technical solution provided in the embodiments of this application, solving the radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel of the infrared detector specifically includes:

[0019] Set temperature range;

[0020] Within the temperature range, select e temperature values, and for each temperature value, select f integration times, where e is a natural number greater than 0, f is a natural number greater than 0, and e×f≥6;

[0021] The blackbody is photographed using an infrared detector to obtain e×f images;

[0022] The radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel point of the infrared detector are solved using e×f images.

[0023] According to the technical solution provided in the embodiments of this application, the temperature range is 5-70 degrees Celsius.

[0024] According to the technical solution provided in the embodiments of this application, when solving the radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel point of the infrared detector using e×f images, the radiometric calibration model is simplified as follows:

[0025] Will Let it be A ij , Let it be B ij ;

[0026] The radiation calibration model can then be expressed as follows:

[0027] Y ij (T b )=t int ·A ij +B ij .

[0028] According to the technical solution provided in the embodiments of this application, the least squares method is used to apply A. ij With B ij Solve the problem.

[0029] According to the technical solution provided in the embodiments of this application, the correction of the image captured by the infrared detector based on the radiometric calibration model and the average radiometric calibration model specifically includes:

[0030] Infrared detectors are used to capture images of the scene, resulting in real-time images;

[0031] The gray value Y of each pixel in the real-time image ij Integration time t int Substitute these values ​​into their respective radiometric calibration models to solve for the temperature value T of each pixel. b ;

[0032] If T b If the value Y has two complex roots, then the pixel is determined to be a bad pixel. That is, the average radiometric calibration model is used as the radiometric calibration model for the pixel, and the gray value Y of the pixel is... ij Integration time t int Substitute the values ​​into the average radiation calibration model to solve for the temperature value of that pixel.

[0033] If T b If there is one complex root and one real root, then the real root is taken as the temperature value of that pixel.

[0034] If T b If there are two real roots, then the real root that falls within the temperature range is selected as the temperature value of that pixel.

[0035] The temperature value T of each pixel point b Substitute this value into the average radiometric calibration model to calculate the gray value Y of each pixel. ij This creates a grayscale image.

[0036] According to the technical solution provided in the embodiments of this application, the NU index is used to measure the uniformity of the grayscale image;

[0037] The formula for calculating NU is as follows:

[0038]

[0039] Where: V avg This represents the average grayscale value in the entire grayscale image.

[0040] d represents the number of bad pixels;

[0041] h represents the number of overheated pixels;

[0042] M and N are the row and column numbers of the infrared detector, respectively;

[0043] V ij This represents the voltage at pixel (i, j) of the infrared detector;

[0044] If the value of NU is between 0.2 and 0.5, it means that the grayscale image meets the non-uniformity index of the infrared imaging system.

[0045] According to the technical solution provided in the embodiments of this application, the set threshold range is 0.2-0.5.

[0046] Compared with existing technologies, the beneficial effects of this application are as follows: This application establishes a radiometric calibration model, solves for the radiometric calibration coefficients in the model, and substitutes the average radiometric calibration coefficients into the model to obtain the average radiometric calibration equation. Based on the radiometric calibration equation and the average radiometric calibration equation, images captured by an infrared detector can be corrected. In practice, it is necessary to first establish equations, use an infrared detector to capture images, and solve for the radiometric calibration equation and the average radiometric calibration equation based on the captured images. These two equations are then used to correct the images captured by the infrared detector. This application, by establishing the radiometric calibration equation and the average radiometric calibration equation, can correct non-uniform images captured by an infrared detector. Verification shows that the corrected images captured by the infrared detector are uniform images. Attached Figure Description

[0047] Figure 1 This application provides a non-uniform correction method for a wide-temperature-range continuously adjustable integral time. Detailed Implementation

[0048] To enable those skilled in the art to better understand the technical solution of this application, the application will be described in detail below with reference to the accompanying drawings. The description in this section is only exemplary and explanatory, and should not be used to limit the scope of protection of this application.

[0049] Please refer to Figure 1 This embodiment provides a non-uniform correction method with continuously adjustable integration time over a wide temperature range, including:

[0050] Let the independent variable be T b t int The function value is Y ij A radiation calibration model, wherein the radiation calibration model has a set of radiation calibration coefficients;

[0051] Specifically, in this embodiment, the expression of the radiation calibration model is as follows:

[0052]

[0053] Where: Y ij This represents the grayscale value of a pixel.

[0054] a ij b ij c ij d ij e ij f ij These are correction factors; six correction factors form a set of radiation calibration factors.

[0055] t int The integration time;

[0056] T b The temperature value of the pixel;

[0057] i is the row number of the pixel, which is a natural number greater than 0;

[0058] j is the column number of the pixel, which is a natural number greater than 0.

[0059] The radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel of the infrared detector are solved to obtain multiple sets of radiometric calibration coefficients;

[0060] Specifically, in this embodiment, the first step is to select a temperature range for calibration. The selected temperature range is -10℃ to 70℃. Within the temperature range, e temperature values ​​are selected, and f integration times are selected for each temperature value, where e is a natural number greater than 0, f is a natural number greater than 0, and e×f≥6.

[0061] In this embodiment, blackbody temperature points of 5℃ and 20℃ are selected within the temperature range of -10℃ to 70℃ for sampling. The integration time selected for the blackbody temperature of 5℃ is set to 16ms, 17ms, and 18ms; the integration time selected for the blackbody temperature of 20℃ is set to 10ms, 14ms, and 18ms. An infrared detector is used to photograph the target object, i.e., the blackbody, and a total of 6 images are acquired. The radiometric calibration equation is established for each pixel in each image. It should be noted that in this embodiment, the radiometric calibration model and the radiometric calibration equation are the same concept.

[0062] The infrared detector in this embodiment contains 640×512 pixels, that is, the pixel array of the captured infrared image is 640×512, that is, the total number of columns of the pixel array of the infrared image is 640 and the total number of rows is 512, that is, i is a natural number greater than 0 and less than or equal to 512, and j is a natural number greater than 0 and less than or equal to 640.

[0063] A uniform blackbody was photographed using an infrared detector, resulting in six images. Because the blackbody was photographed using an infrared detector with 640×512 pixels, each image has 640×512 pixels. Each pixel in the infrared detector corresponds to a pixel in each image; that is, the first pixel in the first row and first column of the infrared detector corresponds to the first pixel in the first row and first column of each image. A radiometric calibration equation is established for each pixel in the image. Each radiometric calibration equation contains a set of radiometric calibration coefficients, and each set of coefficients contains six correction coefficients, a, b, c, and d. ij b ij c ij d ij e ij and f ij Since each of the aforementioned radiometric calibration equations contains six correction coefficients, and all six correction coefficients are unknowns, six first radiometric calibration equations need to be established to solve for the six correction coefficients. That is, each pixel then has six first radiometric calibration equations. During the solution process, the blackbody temperature T of each pixel in each image can be directly obtained. b Integration time t int and grayscale value Y ij Substitute their respective values ​​into the six first radiation calibration equations to form six second radiation calibration equations containing only the radiation calibration coefficients as unknowns; at this point, the six correction coefficients can be solved.

[0064] To make the correction coefficients more accurate, you can also use 12 images to establish an equation for solving. The specific method is as follows:

[0065] Within a temperature range of -10℃ to 70℃, blackbody temperature points of 5℃, 20℃, 35℃, and 65℃ were sampled. The integration times for the blackbody temperature of 5℃ were set to 16ms, 17ms, and 18ms; for 20℃, 10ms, 14ms, and 18ms; for 35℃, 4ms, 11ms, and 15ms; and for 65℃, 3ms, 5ms, and 7ms. An infrared detector was used to photograph the target object, which is the aforementioned blackbody. The blackbody is a uniform blackbody. A total of e×f images (12 images) were acquired. The radiometric calibration equation was established for each pixel in each image. For ease of explanation, an example is given below:

[0066] A uniform blackbody was photographed using an infrared detector, resulting in 12 images. Each image contains 640×512 pixels. Each pixel in the infrared detector corresponds to a pixel in each image; that is, the first pixel in the first row and first column of the infrared detector corresponds to the first pixel in the first row and first column of each image. A radiometric calibration equation was established for each pixel in the image, resulting in 640×512 radiometric calibration equations per image. Each radiometric calibration equation contains a set of radiometric calibration coefficients, and each set of coefficients includes six correction coefficients, each a... ij b ij c ij d ij e ij and f ij Since each of the aforementioned radiometric calibration equations contains six aforementioned correction coefficients, and all six of the aforementioned correction coefficients are unknowns, it is necessary to establish six first radiometric calibration equations to solve for the six aforementioned correction coefficients. That is, each pixel point has six first radiometric calibration equations at this time.

[0067] During the solution process, the blackbody temperature T of each pixel in each image can be directly obtained. b Integration time t int and grayscale value Y ij Substitute their respective values ​​into the six first radiation calibration equations to form six second radiation calibration equations containing only the calibration coefficients as unknowns.

[0068] To facilitate the solution, the correction coefficients can be simplified at this point, that is, the coefficients in the second radiation calibration equation can be simplified. Let it be A ij , Let it be B ij At this point, the radiation calibration equation can be expressed as Y ij (T b )=t int ·A ij +B ij Use the least squares method on A ij With B ij The solution is obtained using the following expression:

[0069]

[0070] Where: t i Let i represent the integration time for each image (where i is a natural number greater than 0).

[0071] n+1 represents the number of integration times selected at the blackbody temperature, where n≥0;

[0072] This indicates that the entire infrared detector pixel (i,j) is at a blackbody temperature of T. b At that time, the average gray value of each pixel at a certain integration time.

[0073] For A ij With B ij After solving for a, the least squares method is used to apply the solution to a. ij b ij c ij d ij e ij and f ij The value of is calculated using the following formula:

[0074]

[0075]

[0076] After solving the problem twice using the least squares method, all six correction coefficients have been solved, and the radiation calibration model can then be obtained.

[0077] The mean radiation calibration coefficients are obtained by solving the radiation calibration coefficients, thus obtaining the mean radiation calibration model.

[0078] In the above calculations, the correction coefficient corresponding to each pixel has been obtained, and for all pixels in all images, i.e., all 12 images, the coefficient 'a' is calculated. ij Numerical summation and division by all a ij The number can be obtained. same, The algorithm and The algorithm is the same, so it will not be repeated here; After the value is obtained, it is substituted into the radiation calibration equation to obtain the average radiation calibration equation;

[0079] The images captured by the infrared detector are corrected based on the radiometric calibration model and the average radiometric calibration model.

[0080] Specifically, in this embodiment, image correction includes:

[0081] In practical applications, infrared detectors are used to capture images of the external scene, obtaining real-time images. These real-time images contain multiple first pixels, and each first pixel can directly obtain its own grayscale value Y. ij Integration time t int The gray value Y of each pixel is... ij Integration time t int Substituting this into the radiation calibration equation, the radiation calibration equation can now be considered a quadratic equation, where the blackbody temperature T... b As an unknown in this equation, for T b Solve the problem;

[0082] If the solution T is obtained b If the value has two complex roots, then the pixel can be determined to be a bad pixel. In this case, the radiometric calibration equation for that pixel needs to be replaced with the average radiometric calibration equation. The average radiometric calibration equation is used as the radiometric calibration equation for that pixel, and the gray value Y of that pixel is set accordingly. ij Integration time t int Substitute this into the replaced mean radiation calibration equation and solve for the temperature value T of that pixel. b ;

[0083] If the solution T is obtained b If one is a complex root and the other is a real root, then the complex root should be discarded and the real root should be selected as the temperature value of that pixel.

[0084] If the solution T is obtained b If there are two real roots, then it is necessary to select the real root that is in the range of -10℃ to 70℃ as the temperature value of the pixel.

[0085] Then solve for each T b Substituting into the average radiometric calibration equation, we solve for the gray value Y. ij And the calculated grayscale value Y ij Draw it as a grayscale image.

[0086] At this point, it is impossible to determine whether the grayscale image is uniform with the naked eye; the NU metric is needed to measure the uniformity of the grayscale image.

[0087] The formula for calculating the NU index is as follows:

[0088]

[0089] Where: V avg This represents the average grayscale value in the entire grayscale image.

[0090] d represents the number of bad pixels;

[0091] h represents the number of overheated pixels;

[0092] M and N are the row and column numbers of the infrared detector, respectively;

[0093] V ij This represents the voltage at pixel (i, j) of the infrared detector;

[0094] Sum all the gray values ​​and calculate their average value;

[0095] The result can be obtained by substituting the grayscale average value, the number of bad pixels (i.e., bad pixels and complex roots), the number of overheated pixels (i.e., pixels that are not in the temperature range of -10℃ to 70℃), and the number of rows and columns of the infrared detector itself into the formula of the NU index.

[0096] If the value of NU is between 0.2 and 0.5, it means that the grayscale image meets the non-uniformity index of the infrared imaging system.

[0097] This application analyzes the response characteristics of the detector, establishes a radiation calibration model based on a wide temperature range, and proposes a non-uniformity correction method with continuously adjustable integration time, achieving optimal imaging under conditions of arbitrary adjustment of integration time over a large span. Even in supersonic vehicle scenarios, where the rapidly changing background radiation from the rapidly varying fairing due to aerodynamic heating effects can be caused by temperature changes, this application's method allows for arbitrary adjustment of the integration time without detector saturation. Even if calibration parameter mismatches occur during integration time adjustment, the image captured by the infrared detector remains uniform. In practical applications, only one set of correction parameters needs to be stored to convert the input grayscale image into a temperature image. In fact, it transforms the problem of solving the radiation calibration equation into the root problem of a quadratic equation. The obtained temperature image is then mapped back to the corrected grayscale image through simple calculations. Compared with the traditional multi-segment two-point correction method, although the number of stored correction parameters is increased from two to six, it does not require separate division of the integration range and temperature range. Only six parameters are needed to adapt to the full temperature range and full integration range, which greatly saves the storage space of the correction data. Moreover, the input integration time can be arbitrarily controlled and the non-uniformity of the image can be guaranteed.

[0098] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are only preferred embodiments of this application. It should be noted that due to the limitations of written expression, while there are objectively infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this invention, and can also combine the above technical features in an appropriate manner. These improvements, modifications, changes, or combinations, or the direct application of the inventive concept and technical solution to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A non-uniform correction method with continuously adjustable integration time over a wide temperature range, used for correcting images captured by an infrared detector, characterized in that... include; Establish the independent variable as , The function value is A radiation calibration model, wherein the radiation calibration model has a set of radiation calibration coefficients; Solve for the radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel of the infrared detector to obtain multiple sets of radiometric calibration coefficients; A set of average radiometric calibration coefficients is obtained by solving multiple sets of radiometric calibration coefficients. The average radiometric calibration coefficients are then substituted into the radiometric calibration model to obtain the average radiometric calibration model. The images captured by the infrared detector are corrected based on the radiometric calibration model and the average radiometric calibration model. The radiation calibration model is as follows: in: This represents the grayscale value of a pixel. , , , , , These are correction factors; six correction factors form a set of radiation calibration factors. The integration time; The temperature value of the pixel; i is the row number of the pixel, which is a natural number greater than 0; j is the column number of the pixel, which is a natural number greater than 0.

2. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 1, characterized in that, Solving for the radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel of the infrared detector specifically includes: Set temperature range; Within the stated temperature range, select e temperature values, and for each temperature value, select f integration times, where e is a natural number greater than 0, f is a natural number greater than 0, and e... f 6; The blackbody was photographed using an infrared detector to obtain e. f images; Using e The radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel point of the infrared detector are obtained from f images.

3. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 2, characterized in that, The temperature range is -10℃ to 70℃.

4. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 2, characterized in that, Using e When solving for the radiometric calibration coefficients of the radiometric calibration model corresponding to each pixel of the infrared detector from f images, the radiometric calibration model is simplified as follows: Will Recorded as , Recorded as ; The radiation calibration model can then be expressed as follows: 。 5. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 4, characterized in that, Using the least squares method and Solve the problem.

6. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 1, characterized in that, The correction of images captured by the infrared detector based on the radiometric calibration model and the average radiometric calibration model specifically includes: Infrared detectors are used to capture images of the scene, resulting in real-time images; The grayscale value of each pixel in the real-time image Integral time Substitute these values ​​into their respective radiometric calibration models to solve for the temperature value of each pixel. ; like If the number has two complex roots, the pixel is determined to be a bad pixel. That is, the average radiometric calibration model is used as the radiometric calibration model for the pixel, and the gray value of the pixel is... Integral time Substitute the values ​​into the mean radiation calibration model to solve for the temperature value of that pixel. ; like If there is one complex root and one real root, then the real root is taken as the temperature value of that pixel. like If there are two real roots, then the real root that falls within the temperature range is selected as the temperature value of that pixel. The temperature value of each pixel point Substitute the values ​​into the average radiometric calibration model to calculate the gray value of each pixel. This creates a grayscale image.

7. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 6, characterized in that, The uniformity of the grayscale image is measured using the NU index. The formula for calculating NU is as follows: in: This represents the average grayscale value in the entire grayscale image. d represents the number of bad pixels; h represents the number of overheated pixels; M and N are the row and column numbers of the infrared detector, respectively; This represents the voltage at pixel (i, j) of the infrared detector; If the value of NU is within the set threshold range, it means that the grayscale image meets the non-uniformity index of the infrared imaging system.

8. The non-uniform correction method with continuously adjustable integration time over a wide temperature range according to claim 7, characterized in that, The set threshold range is 0.2-0.5.

Images