Infrared imaging cold radiation effect correction method, system and device and storage medium

Abstract

The invention discloses an infrared imaging cold radiation effect correction method, system and device and a storage medium, belongs to the technical field of infrared image denoising, and solves the problem that the processing result of subsequent operation on an infrared image is interfered due to the fact that scene information near the edge of a light spot of the infrared image cannot be thoroughly suppressed in an existing method. Acquiring an original infrared image comprising the cold radiation light spot; after a plurality of parameters of the Gaussian function are adjusted, an original infrared image is read based on the adjusted Gaussian function, and the read infrared image is preprocessed; fitting the preprocessed infrared image based on a Butterworth function, and constructing a fitting function; constructing cold radiation light spot features of the infrared image based on parameters of the constructed fitting function and a Butterworth function; and performing differential processing on the cold radiation light spot features and the original infrared image to complete correction of the cold radiation light spots in the infrared image.

Description

Technical Field

[0001] The present invention relates to the technical field of infrared image denoising, and in particular to a method, system, device and storage medium for correcting cold radiation effect of infrared imaging. Background Art

[0002] Infrared images have been widely used in a series of aspects related to national economy and people's livelihood, such as environmental monitoring, target recognition, and astronomical observation. When using a cooled infrared camera to shoot a target, when there is a large temperature difference between the infrared camera sensor and the surrounding environment, obvious cold radiation spots often appear in the image. The spots cause the target area to be blurred, seriously affecting the recognition accuracy and image quality of the target. Especially in low temperature environments, cold radiation spots will significantly interfere with the true performance of the target, thereby reducing the usability of the image.

[0003] At present, it is difficult to effectively distinguish the target from the background, which greatly limits the practical application of infrared images in target detection and analysis. Therefore, the solution to the cold radiation phenomenon is still immature, and currently focuses on noise suppression and image smoothing, but lacks in-depth analysis and effective correction methods for the imaging mechanism of cold radiation spots and their specific impact on image quality. Therefore, how to effectively remove cold radiation spots and restore the clarity of the target has become a key technical problem to improve infrared imaging quality and target recognition accuracy.

[0004] In the prior art, after many rounds of research and development, the scientific research team of Changchun University of Science and Technology has disclosed the "correction method, system, device and medium for cold reflection noise in infrared images" in Chinese patent document 202510252165.6. It can accurately fit the shape of cold reflection noise by fitting and denoising the infrared image after smoothing with the Butterworth function, thereby effectively improving the quality of infrared images. However, when this technology first uses the Butterworth function to denoise the infrared image and then uses the Gaussian function to fit and denoise the infrared image, although the Butterworth function can remove the noise in the infrared image, it will also have a certain degree of smoothing effect on the details in the infrared image, such as cold radiation spots and other features. Because its filtering characteristics are smoothly transitioned rather than completely cut off, the scene information near the edge of the spot may not be completely suppressed. Figure 1 As shown, the horizontal axis is the number of rows of infrared image pixels, and the vertical axis is the number of columns of infrared image pixels. Especially when the scene information around the light spot is complex or the noise is high, additional artifacts or peaks are easily formed next to the light spot model, which will interfere with the processing results of subsequent operations on the infrared image.

[0005] In summary, the existing methods will result in the scene information near the edge of the infrared image spot being unable to be completely suppressed, thereby interfering with the processing results of subsequent operations on the infrared image. Summary of the invention

[0006] The present invention solves the problem that the existing method causes the scene information near the edge of the infrared image spot to be unable to be completely suppressed, thereby interfering with the processing result of the subsequent operation on the infrared image.

[0007] The infrared imaging cold radiation effect correction method of the present invention comprises the following steps: Step S1, acquiring an original infrared image including a cold radiation spot; Step S2, after adjusting the multiple parameters of the Gaussian function respectively, reading the original infrared image described in step S1 based on the adjusted Gaussian function, and preprocessing the read infrared image; Step S3, fitting the infrared image preprocessed in step S2 based on the Butterworth function to construct a fitting function; Step S4, constructing the cold radiation spot characteristics of the infrared image based on the parameters of the fitting function constructed in step S3 and the Butterworth function; Step S5, performing differential processing on the cold radiation spot feature described in step S4 and the original infrared image to complete the correction of the cold radiation spot in the infrared image.

[0008] Furthermore, in one embodiment of the present invention, in step S2, the Gaussian function is specifically: ; in, is a Gaussian function, is the amplitude, All are attributes, are the mean values ​​of the attributes, are the standard deviations of the attributes.

[0009] Further, in one embodiment of the present invention, in the step S2, the multiple parameters of the Gaussian function are adjusted respectively, specifically: The standard deviation of the Gaussian function and the filter window are adjusted respectively.

[0010] Furthermore, in one embodiment of the present invention, the standard deviation of the Gaussian function is specifically: ; in, is the standard deviation of the Gaussian function, is the filter window of the Gaussian function, is a positive integer; The filtering window of the Gaussian function is specifically: .

[0011] Further, in one embodiment of the present invention, in the step S2, the preprocessing is specifically: ; in, For preprocessing, is the infrared image information, for The maximum value of Information Pixel The distance from the center of the cold reflection signal, The degree of suppression of scene signals in infrared images.

[0012] Further, in one embodiment of the present invention, in step S3, the Butterworth function is specifically: ; in, is the Butterworth function, and All are attributes, is the amplitude, and are the mean values ​​of the attributes, and are the standard deviations of the attributes.

[0013] Further, in one embodiment of the present invention, in the step S4, the cold radiation spot characteristics of the infrared image are constructed based on the parameters of the fitting function constructed in step S3 and the Butterworth function, specifically: The parameters of the fitting function are used as the cold radiation spot characteristics of the infrared image after fitting in step S3. The Butterworth function maps the infrared image preprocessed in step S2 to form a surface, which is also used as the cold radiation spot characteristics.

[0014] The infrared imaging cold radiation effect correction system of the present invention comprises the following modules: An acquisition module, for acquiring an original infrared image including a cold radiation spot; An adjustment module, after adjusting multiple parameters of the Gaussian function respectively, reads the original infrared image of the acquisition module based on the adjusted Gaussian function, and pre-processes the read infrared image; The fitting module fits the infrared image preprocessed by the adjustment module based on the Butterworth function to construct a fitting function; A construction module, which constructs the cold radiation spot characteristics of the infrared image based on the parameters of the fitting function constructed in the fitting module and the Butterworth function; The correction module performs differential processing on the cold radiation spot characteristics described in the construction module and the original infrared image to complete the correction of the cold radiation spot in the infrared image.

[0015] An electronic device described in the present invention comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory, used to store computer programs; The processor is used to implement the infrared imaging cold radiation effect correction method described in any of the above methods when executing the program stored in the memory.

[0016] The present invention discloses a computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium. When the computer program is executed by a processor, the infrared imaging cold radiation effect correction method described in any of the above methods is implemented.

[0017] The present invention solves the problem that the existing method causes the scene information near the edge of the infrared image spot to be unable to be completely suppressed, thereby interfering with the processing results of the subsequent operation on the infrared image. Specific beneficial effects include: 1. The infrared imaging cold radiation effect correction method described in the present invention, the existing processing method will result in the scene information near the edge of the infrared image spot cannot be completely suppressed, thereby interfering with the subsequent operation of the infrared image processing results. In order to solve the above technical problems, the present invention first uses a Gaussian function to read the infrared image, which can more flexibly select and retain useful scene information, thereby not interfering with the operation of fitting the infrared image through the Butterworth function; 2. The infrared imaging cold radiation effect correction method described in the present invention, after reading the infrared image through the Gaussian function, when the Butterworth function is used to fit the infrared image, it needs to be manually adjusted according to the spot shape, which will cause the problem of fluctuations in the processing effect in different scenes. In order to overcome the above technical difficulties, the present invention adjusts multiple parameters of the Gaussian function, and then performs the above operations based on the adjusted parameters, so that the processing results of the method described in the present invention in different scenes are in a stable state; The infrared imaging cold radiation effect correction method of the present invention can effectively remove the cold radiation spot noise in the infrared image, thereby improving the quality and resolution of the infrared image. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is the effect diagram of the infrared image processed by the Butterworth function described in the background technology; Figure 2 The first original infrared image containing the cold radiation spot described in the first embodiment; Figure 3 The first embodiment uses the Butterworth function to extract the cold radiation spot, and then fits the Gaussian function. Figure 2 The result of subtracting the original infrared image containing the cold radiation spot is shown; Figure 4 The first embodiment described in Figure 2 The original infrared image corresponding to the first original infrared image containing the cold radiation spot; Figure 5 The first embodiment described Figure 4 and Figure 3 The result diagram after difference; Figure 6 This is a result diagram of the existing processing method described in the first embodiment; Figure 7 is a result diagram of the processing method of this embodiment described in the first embodiment; Figure 8 The second original infrared image containing the cold radiation spot described in the first embodiment; Fig. 9 The Gaussian function is used to extract the cold radiation spot as described in the first embodiment, and then the Butterworth function is fitted. Figure 8 The result of subtracting the original infrared image containing the cold radiation spot is shown; Fig.10 The first embodiment described in Figure 8 The original infrared image corresponding to the second original infrared image containing the cold radiation spot; Fig.11 The first embodiment described Fig.10 and Fig. 9 The result diagram after difference. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe various embodiments of the present invention in conjunction with the accompanying drawings. The embodiments described with reference to the accompanying drawings are exemplary and intended to be used to explain the present invention, but should not be understood as limiting the present invention.

[0020] Embodiment 1: The infrared imaging cold radiation effect correction method described in this embodiment includes the following steps: Step S1, acquiring an original infrared image including a cold radiation spot; Step S2, after adjusting the multiple parameters of the Gaussian function respectively, reading the original infrared image described in step S1 based on the adjusted Gaussian function, and preprocessing the read infrared image; Step S3, fitting the infrared image preprocessed in step S2 based on the Butterworth function to construct a fitting function; Step S4, constructing the cold radiation spot characteristics of the infrared image based on the parameters of the fitting function constructed in step S3 and the Butterworth function; Step S5, performing differential processing on the cold radiation spot feature described in step S4 and the original infrared image to complete the correction of the cold radiation spot in the infrared image.

[0021] In this implementation manner, in step S2, the Gaussian function is specifically: ; in, is a Gaussian function, is the amplitude, All are attributes, are the mean values ​​of the attributes, are the standard deviations of the attributes.

[0022] In this implementation manner, in the step S2, the multiple parameters of the Gaussian function are adjusted respectively, specifically: The standard deviation of the Gaussian function and the filter window are adjusted respectively.

[0023] In this implementation manner, the standard deviation of the Gaussian function is specifically: ; in, is the standard deviation of the Gaussian function, is the filter window of the Gaussian function, is a positive integer; The filtering window of the Gaussian function is specifically: .

[0024] In this implementation manner, in the step S2, the preprocessing is specifically as follows: ; in, For preprocessing, is the infrared image information, for The maximum value of Information Pixel The distance from the center of the cold reflection signal, The degree of suppression of scene signals in infrared images.

[0025] In this implementation manner, in step S3, the Butterworth function is specifically: ; in, is the Butterworth function, and All are attributes, is the amplitude, and are the mean values ​​of the attributes, and are the standard deviations of the attributes.

[0026] In this embodiment, in the step S4, the cold radiation spot characteristics of the infrared image are constructed based on the parameters of the fitting function constructed in step S3 and the Butterworth function, specifically: The parameters of the fitting function are used as the cold radiation spot characteristics of the infrared image after fitting in step S3. The Butterworth function maps the infrared image preprocessed in step S2 to form a surface, which is also used as the cold radiation spot characteristics.

[0027] Chinese patent document 202510252165.6 discloses "correction method, system, device and medium for cold reflection noise in infrared images". However, although the Butterworth function can remove the light spots in the infrared image, it will also have a certain degree of smoothing effect on the cold radiation light spots in the infrared image. Because its filtering characteristics are smooth transitions rather than completely cut off, the scene information near the edge of the light spot may not be completely suppressed. Especially when the scene information around the light spot is complex or the noise is high, it is easy to form additional artifacts or peaks next to the light spot model, which will interfere with the processing results of the infrared image by subsequent operations.

[0028] In order to solve the above technical problems, this embodiment proposes a method for correcting cold radiation effect of infrared imaging, comprising the following steps: Step S1, in the selected scene, use the cooling type infrared imaging system to collect infrared images and obtain the original infrared image containing the cold radiation spot .

[0029] Step S2, respectively adjusting the standard deviation and the filter window of the Gaussian function, and reading the original infrared image described in step S1 based on the adjusted filter window of the Gaussian function , remove unnecessary scene information, and then read the infrared image Preprocessing is performed to maximize the retention of information around cold radiation while suppressing and eliminating the remaining information, thereby minimizing the scene information of the infrared image; The Gaussian function is specifically: ; in, is a Gaussian function, is the amplitude, All are attributes, are the mean values ​​of the attributes, are the standard deviations of the attributes.

[0030] It should be noted that in this embodiment, the original infrared image is read in the filter window using the Gaussian function. Previously, it was necessary to adjust the standard deviation of the Gaussian function and the size of the filter window separately. The essential reason is that when the infrared image is first read with the Gaussian function and then fitted with the Butterworth function, the parameters of the original Gaussian function need to be manually adjusted according to the spot shape. The lack of an adaptive mechanism leads to fluctuations in the processing effect in different scenes. Therefore, in order to solve the above technical problems, this embodiment adjusts the standard deviation of the Gaussian function and the filter window separately, specifically: The larger the standard deviation of the Gaussian function, the higher the smoothness of the infrared image by the filter, but it may cause the loss of infrared image details. The smaller the standard deviation of the Gaussian function, the more infrared image details are retained, but the light spot suppression effect is weaker. In order to solve the problem that when the filter reads the infrared image, the infrared image details are not lost and the light spot can be effectively suppressed, the standard deviation of the Gaussian function is defined as: ; in, is the standard deviation of the Gaussian function, which is used to control the diffusion degree of the Gaussian function. is the filtering window of the Gaussian function, which determines the range covered by the Gaussian function. is 1, 2, 3..., which can dynamically adjust the window size to avoid causing too much interference to the edge area of ​​the infrared image.

[0031] The larger the filter window of the Gaussian function, the wider the filter coverage, and the ability to process large-area noise, but it may affect the calculation efficiency. The smaller the filter window of the Gaussian function, the higher the calculation efficiency, but the ability to process the surrounding details of the light spot is insufficient. Similarly, in order to solve the problem that the filter improves the calculation efficiency of the infrared image while improving the ability to process the surrounding details of the light spot when reading the infrared image, and also ensures that the filter window sufficiently covers the distribution range of the Gaussian function, the filter window of the Gaussian function is defined as: .

[0032] Therefore, this embodiment can make the Gaussian function more stable in different scenes when reading infrared images by adjusting the standard deviation and filter window of the Gaussian function respectively. In addition, the infrared image can be effectively reduced by the Gaussian function to reduce the residual noise around the spot and prevent the appearance of pseudo peaks.

[0033] The infrared image after reading is preprocessed to reconstruct the details lost in the smoothing process and maintain the integrity of the infrared image. The preprocessing is specifically as follows: ; in, For preprocessing, is the infrared image information, is the maximum gray value of the mean infrared image or The maximum value of Information Pixel Cold reflex signal center The distance between , is the standard deviation in the mean infrared image, that is, the degree of suppression of the scene signal in the infrared image.

[0034] Step S3, fitting the preprocessed infrared image in step S2 based on the Butterworth function to construct a fitting function.

[0035] Specifically, the Butterworth function provides an ideal mathematical model. In order to make the Butterworth function as consistent as possible with the actual data of the cold radiation spot in the infrared image, it needs to be completed through a fitting process. Therefore, the least squares method is needed to optimize and solve the optimal parameters of the function in the fitting process. The least squares method adjusts the parameters of the Butterworth function by minimizing the sum of squares of the error between the fitting function and the actual data of the infrared image, so that the fitting result is as close as possible to the distribution of the real infrared image.

[0036] The construction of the fitting function comprises the following steps: Step S301, using Butterworth function as a mathematical model; Step S302, by using the cold radiation areas retained by preprocessing as fitting targets, the pixel values ​​of these areas can be used to fit the Butterworth function; Step S303, in order to make the Butterworth function match the infrared image data as much as possible, it is necessary to adjust the parameters in the Butterworth function using the pixel information in the infrared image; Step S304, by adjusting the parameters in the Butterworth function so that it can fit the infrared image data most accurately, the construction of the fitting function is completed.

[0037] The Butterworth function is specifically: ; in, is the Butterworth function, and All are attributes, is the amplitude, and are the mean values ​​of the attributes, and are the standard deviations of the attributes.

[0038] Will , , , and Initialized to 1, using least squares matrix operations, adjust , , , and Until the fitting accuracy reaches the threshold, the parameters of the fitting function are obtained.

[0039] The Butterworth function performs secondary optimization on the result after Gaussian function preprocessing to further improve the quality of infrared images and avoid artifact interference.

[0040] Step S4, the parameters of the fitting function are used as the cold radiation spot characteristics of the infrared image after fitting described in step S3, and the Butterworth function is used to map the infrared image after preprocessing described in step S2 to form a surface, and the surface is also used as the cold radiation spot characteristics.

[0041] Step S5, performing differential processing on the cold radiation spot feature described in step S4 and the original infrared image, removing the spot in the infrared image, clearly distinguishing the infrared image from the background, and improving the quality of the infrared image.

[0042] Therefore, in the infrared image processing process, this embodiment first uses a Gaussian function to process the cold radiation spot area to suppress the spot and retain the main features of the spot model, and then uses a Butterworth function for further refinement to more accurately remove the remaining spots.

[0043] In order to better illustrate the infrared imaging cold radiation effect correction method described in this embodiment, a detailed description is given through the following examples: like Figure 2 As shown in the figure, it is the first original infrared image containing the cold radiation spot. Figure 3 As shown in the figure, the cold radiation spot is extracted using the Butterworth function, and then the Gaussian function is fitted. Figure 2 The result of subtracting the original infrared image containing the cold radiation spot is shown in Figure 4 As shown, Figure 2 The original infrared image corresponding to the second original infrared image containing the cold radiation spot is as follows: Figure 5 As shown, Figure 4 and Figure 3From the difference results, we can see that using the Butterworth function as a preprocessor will result in the removal of some useful information in the scene.

[0044] like Figure 8 As shown in the figure, it is the second original infrared image containing the cold radiation spot. Fig. 9 As shown in the figure, the cold radiation spot is extracted using the Gaussian function, and then the Butterworth function is fitted. Figure 8 The result of subtracting the original infrared image containing the cold radiation spot is shown in Fig.10 As shown, Figure 8 The original infrared image corresponding to the second original infrared image containing the cold radiation spot is as follows: Fig.11 As shown, Fig.10 and Fig. 9 From the difference results, it can be seen that using the Gaussian function as a preprocessing method can completely remove the cold radiation spot and retain the surrounding scene as much as possible.

[0045] like Figure 6 As shown in the figure, it is the result of using the existing processing method. It can be seen that there is a lot of scene information near the center of the infrared image, which will lead to poor results in the subsequent cold radiation spot extraction. Figure 7 As shown, it is the result of the processing method of this embodiment. It can be seen that the scene information around the center of the cold radiation spot is basically completely eliminated, and the cold radiation spot information is retained with a great probability, but there is still a trace amount of scene information. At this time, the Butterworth function is used to fit and extract the processed infrared image, which can completely remove the scene information and improve the image quality and resolution.

[0046] In summary, this embodiment effectively solves the problem that the existing method causes the scene information near the edge of the infrared image spot to be unable to be completely suppressed, thereby interfering with the processing results of the subsequent operation on the infrared image by using the Gaussian function and the Butterworth function in sequence. At the same time, by adjusting multiple parameters of the Gaussian function, the results of this processing method are made more stable.

[0047] Embodiment 2: The infrared imaging cold radiation effect correction system described in this embodiment includes the following modules: An acquisition module, for acquiring an original infrared image including a cold radiation spot; An adjustment module, after adjusting multiple parameters of the Gaussian function respectively, reads the original infrared image of the acquisition module based on the adjusted Gaussian function, and pre-processes the read infrared image; The fitting module fits the infrared image preprocessed by the adjustment module based on the Butterworth function to construct a fitting function; A construction module, which constructs the cold radiation spot characteristics of the infrared image based on the parameters of the fitting function constructed in the fitting module and the Butterworth function; The correction module performs differential processing on the cold radiation spot characteristics described in the construction module and the original infrared image to complete the correction of the cold radiation spot in the infrared image.

[0048] Embodiment 3: An electronic device described in this embodiment includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor is used to implement the infrared imaging cold radiation effect correction method described in implementation mode 1 when executing the program stored in the memory.

[0049] Embodiment 4: This embodiment describes a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the infrared imaging cold radiation effect correction method described in embodiment 1 is implemented.

[0050] The above is a detailed introduction to the infrared imaging cold radiation effect correction method, system, device and storage medium proposed in the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for correcting cold radiation effect of infrared imaging, characterized in that: The following steps are involved: Step S1, acquiring an original infrared image including a cold radiation spot; Step S2, after adjusting the multiple parameters of the Gaussian function respectively, reading the original infrared image described in step S1 based on the adjusted Gaussian function, and preprocessing the read infrared image; Step S3, fitting the infrared image preprocessed in step S2 based on the Butterworth function to construct a fitting function; Step S4, constructing the cold radiation spot characteristics of the infrared image based on the parameters of the fitting function constructed in step S3 and the Butterworth function; Step S5, performing differential processing on the cold radiation spot feature described in step S4 and the original infrared image to complete the correction of the cold radiation spot in the infrared image.

2. The infrared imaging cold radiation effect correction method according to claim 1, characterized in that: In the step S2, the Gaussian function is specifically: ； in, is a Gaussian function, is the amplitude, All are attributes, are the mean values ​​of the attributes, are the standard deviations of the attributes.

3. The infrared imaging cold radiation effect correction method according to claim 1, characterized in that: In the step S2, the multiple parameters of the Gaussian function are adjusted respectively, specifically: The standard deviation of the Gaussian function and the filter window are adjusted respectively.

4. The infrared imaging cold radiation effect correction method according to claim 3, characterized in that: The standard deviation of the Gaussian function is specifically: ； in, is the standard deviation of the Gaussian function, is the filter window of the Gaussian function, is a positive integer; The filtering window of the Gaussian function is specifically: 。 5. The infrared imaging cold radiation effect correction method according to claim 1, characterized in that: In the step S2, the pre-processing is specifically: ； in, For preprocessing, is the infrared image information, for The maximum value of Information Pixel The distance from the center of the cold reflection signal, The degree of suppression of scene signals in infrared images.

6. The infrared imaging cold radiation effect correction method according to claim 1, characterized in that: In the step S3, the Butterworth function is specifically: ； in, is the Butterworth function, and All are attributes, is the amplitude, and are the mean values ​​of the attributes, and are the standard deviations of the attributes.

7. The infrared imaging cold radiation effect correction method according to claim 1, characterized in that: In the step S4, the cold radiation spot characteristics of the infrared image are constructed based on the parameters of the fitting function constructed in step S3 and the Butterworth function, specifically: The parameters of the fitting function are used as the cold radiation spot characteristics of the infrared image after fitting in step S3. The Butterworth function maps the infrared image preprocessed in step S2 to form a surface, which is also used as the cold radiation spot characteristics.

8. Infrared imaging cold radiation effect correction system, characterized in that: Includes the following modules: An acquisition module, for acquiring an original infrared image including a cold radiation spot; An adjustment module, after adjusting multiple parameters of the Gaussian function respectively, reads the original infrared image of the acquisition module based on the adjusted Gaussian function, and pre-processes the read infrared image; The fitting module fits the infrared image preprocessed by the adjustment module based on the Butterworth function to construct a fitting function; A construction module, which constructs the cold radiation spot characteristics of the infrared image based on the parameters of the fitting function constructed in the fitting module and the Butterworth function; The correction module performs differential processing on the cold radiation spot characteristics described in the construction module and the original infrared image to complete the correction of the cold radiation spot in the infrared image.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor is used to implement the infrared imaging cold radiation effect correction method described in any one of claims 1-7 when executing the program stored in the memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the infrared imaging cold radiation effect correction method according to any one of claims 1 to 7 is implemented.

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