A method and system for luminance homogenization of a sequence of images of aerodynamic heat radiation effects

Abstract

The present invention belongs to the technical field of digital image processing, and discloses a method and a system for brightness homogenization of an image sequence of pneumatic thermal radiation effects. The method includes: constructing a weight function of the bias field fitting coefficient vector based on the bias field fitting coefficient vector of each degraded image in the degraded image sequence; constructing a sparse vector of the bias field of each degraded image by using the weight function: fitting the bias field of each degraded image; subtracting the fitted bias field corresponding to each degraded image from each degraded image to obtain a corrected image for each frame, so as to achieve brightness homogenization of the degraded image sequence. Further, by constructing a fitting function based on the gray distribution of the image sequence for each corrected image, and replacing the mean value of the corresponding corrected image with the fitting function, an updated corrected image is obtained, so as to achieve further brightness homogenization of the degraded image sequence. The present invention can homogenize the brightness of an image sequence of pneumatic thermal radiation effects.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital image processing, and more specifically, relates to a method and system for uniformizing the brightness of an image sequence of an aerodynamic heat radiation effect. Background Art

[0002] When an aircraft carrying an imaging system flies in the atmosphere, the optical dome rubs against the high-speed oncoming flow and heats up, inducing an aerodynamic heat radiation effect similar to "halo" on the image plane, deteriorating the signal-to-noise ratio of the target image.

[0003] Existing correction technologies mainly focus on the statistical modeling of the bias field degradation characteristics of the aerodynamic heat radiation effect, and use various polynomial fitting methods to estimate the shape of the bias field surface to correct the degraded image. These methods have good correction effects for single-frame images, but the correction effects for image sequences are limited. Specifically, the corrected image sequence shows a screen flashing phenomenon, that is, the brightness of the corrected image sequence is uneven. Summary of the Invention

[0004] In view of the above defects or improvement requirements of the existing technology, the present invention provides a method and system for uniformizing the brightness of an image sequence of an aerodynamic heat radiation effect, aiming to uniformize the brightness of the image sequence of the aerodynamic heat radiation effect.

[0005] To achieve the above object, according to the first aspect of the present invention, a method for uniformizing the brightness of an image sequence of an aerodynamic heat radiation effect is provided, including:

[0006] Constructing a weight function of the bias field fitting coefficient vector based on the bias field fitting coefficient vector of each frame of degraded image in the degraded image sequence; wherein, the weight function is used to associate the bias field fitting coefficient vectors of an n-frame degraded image sequence;

[0007] Constructing a sparse vector of the bias field of each frame of degraded image with the weight function:

[0008]

[0009] where a i ' represents the sparse vector of the bias field of the i-th frame of degraded image X i , a j represents the bias field fitting coefficient vector of the j-th frame of degraded image, and k j represents the weight function of the bias field fitting coefficient vector of the j-th frame of degraded image;

[0010] Fitting the bias field of each frame of degraded image: B i = Wa i ', where B i represents the bias field of the i-th frame of degraded image X iThe bias field, and W is the dictionary used to obtain the fitting coefficient vector of the bias field;

[0011] Subtract the corresponding fitted bias field from each frame of the degraded image to obtain each frame of corrected image, so as to realize the brightness uniformity of the degraded image sequence.

[0012] Further, the weight function is:

[0013]

[0014] where a i represents the bias field fitting coefficient vector of the i-th frame of degraded image X i , k i represents the weight function of the bias field fitting coefficient vector a i , and 1 represents the L1 norm.

[0015] Further, obtaining the bias field fitting coefficient vector of the aerodynamic heat radiation effect for each frame of the degraded image sequence includes:

[0016] Adopt the polynomial fitting method of the aerodynamic heat radiation effect field to fit the bias field of each frame of the degraded image sequence, and obtain the bias field fitting coefficient vector of the aerodynamic heat radiation effect of each frame of the degraded image.

[0017] Further, after obtaining the corrected image, it further includes:

[0018] Construct the fitting function based on the gray distribution of the image sequence for each frame of the corrected image:

[0019]

[0020]

[0021] In the formula, g i represents the fitting function based on the gray distribution of the image sequence of the i-th frame of corrected image Z i ; k t represents the fitting coefficient; Z m (p,q) is the gray value of the corrected image Z m at (p,q), Z t (p,q) is the gray value of the corrected image Z t at (p,q), and w and h respectively represent the width and height of each frame of the corrected image;

[0022] Replace the mean value of the corresponding corrected image with the fitting function to obtain the updated corrected image, so as to further realize the brightness uniformity of the degraded image sequence.

[0023] According to the second aspect of the present invention, there is provided a system for uniformizing the brightness of an image sequence of pneumatic thermal radiation effects, including:

[0024] A weight function construction module, configured to construct a weight function of the bias field fitting coefficient vector based on the pneumatic thermal radiation effect bias field fitting coefficient vector of each frame of the degraded image sequence; wherein, the weight function is used to associate the bias field fitting coefficient vectors of the n-frame degraded image sequence;

[0025] A bias field sparse vector construction module, configured to construct a bias field sparse vector of each frame of the degraded image with the weight function:

[0026]

[0027] wherein, a i ' represents the bias field sparse vector of the i-th frame of the degraded image X i , a j represents the bias field fitting coefficient vector of the j-th frame of the degraded image, and k j represents the weight function of the bias field fitting coefficient vector of the j-th frame of the degraded image;

[0028] A bias field fitting module, configured to fit the bias field of each frame of the degraded image: B i = Wa i ', wherein, B i represents the bias field of the i-th frame of the degraded image X i , and W is the dictionary used to obtain the bias field fitting coefficient vector;

[0029] A first brightness uniformization module, configured to subtract the corresponding fitted bias field from each frame of the degraded image to obtain each frame of corrected image, so as to realize the brightness uniformization of the degraded image sequence.

[0030] Further, the weight function is:

[0031]

[0032] wherein, a i represents the bias field fitting coefficient vector of the i-th frame of the degraded image X i , k i represents the weight function of the bias field fitting coefficient vector a i , and 1 represents the L1 norm.

[0033] Further, it further includes:

[0034] A fitting function construction module, configured to construct a fitting function based on the gray distribution of the image sequence for each frame of the corrected image:

[0035]

[0036]

[0037] wherein, g i represents the fitting function of the i-th frame corrected image Z i based on the gray-scale distribution of the image sequence; k t represents the fitting coefficient; Z m (p, q) is the gray-scale value of the corrected image Z m at (p, q), and Z t (p, q) is the gray-scale value of the corrected image Z t at (p, q), where w and h respectively represent the width and height of each frame of the corrected image;

[0038] The second luminance equalization module is configured to replace the mean value of the corresponding corrected image with the fitting function to obtain an updated corrected image, thereby further equalizing the luminance of the degraded image sequence.

[0039] According to a third aspect of the present invention, there is provided an electronic device, including a computer-readable storage medium and a processor;

[0040] The computer-readable storage medium is configured to store executable instructions;

[0041] The processor is configured to read the executable instructions stored in the computer-readable storage medium and execute the pneumatic thermal radiation effect image sequence luminance equalization method according to any one of the first aspects.

[0042] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the pneumatic thermal radiation effect image sequence luminance equalization method according to any one of the first aspects.

[0043] According to a fifth aspect of the present invention, there is provided a computer program product, including a computer program, and when the computer program runs on a computer, it causes the computer to execute the pneumatic thermal radiation effect image sequence luminance equalization method according to any one of the first aspects.

[0044] Generally speaking, through the above technical solutions conceived by the present invention, the following beneficial effects can be achieved:

[0045] (1) Through analysis, one of the reasons for the uneven brightness of the corrected image sequence is the sudden change in the fitting bias field surface between adjacent frames in the image sequence. That is, the existing polynomial fitting method for the bias field of the aerodynamic heat radiation effect only applies a smoothing constraint to the gradient of a single-frame image and does not consider the smooth change of the image sequence over time, resulting in a large change in the gray level of the estimated bias field over time. Moreover, the polynomial fitting method represents the bias field through a coefficient vector and a dictionary, but the sparse coefficient vector is greatly affected by factors such as noise, leading to unstable estimation of the bias field (the noise points in the coefficient vector cause inaccurate surface fitting). Based on this discovery, in the present invention, a weight function for correlating the bias field fitting coefficient vectors of multiple frames of degraded image sequences is proposed. Based on this weight function, a sparse vector of the bias field for each frame of the degraded image is constructed to add a global constraint to the bias field fitting coefficient vector of the aerodynamic heat radiation effect (this sparse vector of the bias field correlates the bias field fitting coefficient vectors of consecutive n frames of degraded images starting from the current frame of the degraded image), avoiding sudden changes in the bias field surface between adjacent frames caused by noise points in the coefficient vector and preventing obvious jumps in the bias field between adjacent frames, ensuring the gray level stability of the reconstructed field sequence.

[0046] (2) Preferably, the weight function of the bias field fitting coefficient vector constructed in the present invention utilizes the property of the L1 norm to promote sparse solutions, reducing the influence of noise and redundant information. Moreover, the numerator of this weight function is the L1 norm representing the bias field fitting coefficient vector a i of the i-th frame of the degraded image X i , retaining the key field information. At the same time, the denominator globally correlates the bias field fitting coefficient vectors of multiple frames, avoiding obvious jumps in the bias field between adjacent frames.

[0047] (3) Further, through analysis, another reason for the uneven brightness of the corrected image sequence is the uneven gray level transition of the corrected image sequence. That is, the existing polynomial fitting method for the bias field of the aerodynamic heat radiation effect only considers removing the infrared heat radiation effect field, and it is difficult for the corrected image sequence to maintain consistent brightness globally, with poor gray level retention compared to the original image sequence. Based on this discovery, in the present invention, the gray level mean of the corrected image sequence is correlated. Specifically, a gray level mean fitting function based on the gray level distribution of the image sequence is constructed to replace the mean of the corrected image sequence, eliminating the gray level fluctuations that occur in the corrected image sequence. This gray level mean fitting function models the gray level information of consecutive n frames of corrected images starting from the current frame, smoothes the gray level transition, and utilizes the global gray level distribution characteristics of the image sequence to make the corrected image sequence maintain consistent brightness globally and improve the stability of the gray level distribution of the corrected image sequence.

[0048] In summary, the present invention constructs a weight function based on the polynomial fitting coefficients of the pneumatic thermal radiation effect field to stably fit the offset field surface and equalize the grayscale of the image sequence. Further, a grayscale mean fitting function based on the grayscale distribution of the image is constructed to smoothly correct the grayscale transition of the image sequence, so that the corrected image sequence can maintain consistent brightness globally. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the method for equalizing the brightness of the pneumatic thermal radiation effect image sequence in the embodiment of the present invention.

[0050] Figure 2 It is a comparison of the infrared image grayscale mean retention effects in the embodiment of the present invention.

[0051] Figure 3 It is a comparison of the visualization effects with and without using the brightness equalization technique in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0053] Embodiment 1

[0054] As Figure 1 shown, the embodiment of the present invention provides a method for equalizing the brightness of a pneumatic thermal radiation effect image sequence, which mainly includes:

[0055] S1. Based on the pneumatic thermal radiation effect offset field fitting coefficient vector of each frame of degraded image in the degraded image sequence, construct a weight function of the offset field fitting coefficient vector; this weight function is used to associate the offset field fitting coefficient vectors of n frames of degraded image sequences;

[0056] S2. Use the weight function to construct the offset field sparse vector of each frame of degraded image:

[0057]

[0058] In the formula, a i ' represents the offset field sparse vector of the i-th frame of degraded image X i , a j represents the offset field fitting coefficient vector of the j-th frame of degraded image, and k j represents the weight function of the offset field fitting coefficient vector of the j-th frame of degraded image; n is the number of frames for fusion;

[0059] S3. Fit the bias field of each frame of degraded image: B i = Wa i ', where B i represents the bias field of the i-th frame of degraded image X i , W is the dictionary used to obtain the fitting coefficient vector of the above bias field;

[0060] S4. Subtract the corresponding fitted bias field from each frame of degraded image to obtain each frame of corrected image: Z i = X i - B i , Z i represents the i-th frame of corrected image to achieve brightness uniformity of the degraded image sequence.

[0061] As a preferred implementation, in S1, obtaining the fitting coefficient vector of the aerodynamic heat radiation effect bias field of each frame of degraded image includes:

[0062] Use the polynomial fitting method of the aerodynamic heat radiation effect field to fit the bias field of each frame of degraded image in the degraded image sequence to obtain the fitting coefficient vector of the aerodynamic heat radiation effect bias field of each frame of degraded image.

[0063] As a preferred implementation, in S1, the weight function of the constructed bias field fitting coefficient vector is:

[0064]

[0065] where a i represents the fitting coefficient vector of the bias field of the i-th frame of degraded image X i , k i represents the weight function of the bias field fitting coefficient vector a i , 1 represents the L1 norm, and n is the number of frames for fusion.

[0066] In other embodiments, other weight functions of the bias field fitting coefficient vector can also be selected. For example, corresponding coefficients can be added to the above weight function formula according to actual needs, as long as the weight function can relate to the bias field fitting coefficient vectors of the n-frame degraded image sequence.

[0067] Through analysis, the present invention finds that one of the reasons for the uneven brightness of the corrected image sequence is the sudden change of the fitting bias field surface between adjacent frames in the image sequence. That is to say, the existing polynomial fitting method for the bias field of the aerodynamic heat radiation effect only imposes a smoothing constraint on the gradient of a single-frame image, without considering the smooth change of the image time series. As a result, the estimated bias field has a large gray-scale change in time series, and the polynomial fitting method represents the bias field through a coefficient vector and a dictionary. However, the sparse coefficient vector is greatly affected by factors such as noise, resulting in unstable estimated bias fields (the noise points in the coefficient vector cause inaccurate surface fitting). Based on this discovery, the present invention proposes a weight function for associating the bias field fitting coefficient vectors of multiple frames of degraded image sequences, and constructs a sparse vector of the bias field for each frame of degraded image based on this weight function, so as to add a global constraint to the bias field fitting coefficient vector of the aerodynamic heat radiation effect (this sparse vector of the bias field is associated with the bias field fitting coefficient vectors of consecutive n frames of degraded images starting from the current frame of degraded image), avoiding the sudden change of the bias field surface between adjacent frames caused by the noise points in the coefficient vector, avoiding obvious jumps of the bias field between adjacent frames, and ensuring the gray-scale stability of the reconstructed field sequence.

[0068] Preferably, the weight function of the bias field fitting coefficient vector constructed by the present invention utilizes the property of the L1 norm to promote sparse solutions, reducing the influence of noise and redundant information; moreover, the numerator of this weight function is the L1 norm representing the bias field fitting coefficient vector a i of the i-th frame of degraded image X i , which retains the key field information. At the same time, the denominator globally associates the bias field fitting coefficient vectors of multiple frames, avoiding obvious jumps of the bias field between adjacent frames.

[0069] As a further design of the present invention, after step S4, it further includes:

[0070] S5. Construct a fitting function based on the gray-scale distribution of the image sequence for each frame of the corrected image:

[0071]

[0072]

[0073] In the formula, g i represents the fitting function based on the gray-scale distribution of the image sequence for the i-th frame of the corrected image Z i ; k t represents the fitting coefficient; Z m (p,q) is the gray-scale value of the corrected image Z m at (p,q), Z t (p,q) is the gray-scale value of the corrected image Z t at (p,q), and w and h respectively represent the width and height of each frame of the corrected image.

[0074] S6. Replace the mean value of the corresponding corrected image with a fitting function to obtain an updated corrected image, achieving further brightness uniformity:

[0075] Z stable_i =Z i -mean(Z i )+g i

[0076] In the formula, Z stable_i represents the corrected image of the i-th frame after update, that is, the corrected image with further brightness uniformity; mean(Z i ) is the gray mean value of the i-th frame corrected image.

[0077] After analysis, the present invention finds that the reasons for the uneven brightness of the corrected image sequence also include the uneven gray-scale transition of the corrected image sequence. That is, the existing polynomial fitting method for the bias field of the aerodynamic thermal radiation effect only considers removing the infrared thermal radiation effect field, and it is difficult for the corrected image sequence to maintain consistent brightness globally, and the gray-scale retention with the original image sequence is poor. Based on this discovery, the present invention proposes to correlate the gray mean value of the corrected image sequence. Specifically, a gray mean value fitting function based on the gray-scale distribution of the image sequence is constructed to replace the mean value of the corrected image sequence and eliminate the gray-scale fluctuations in the corrected image sequence. This gray mean value fitting function of the image sequence models the gray-scale information of consecutive n frames of corrected images starting from the current frame, smooths the gray-scale transition, and uses the global gray-scale distribution characteristics of the image sequence to make the corrected image sequence maintain consistent brightness globally and improve the stability of the gray-scale distribution of the corrected image sequence.

[0078] The following further illustrates the present invention with reference to embodiments. As Figure 2 shown, it is a simulation diagram comparing the gray mean values of the frame sequences of the image itself with unchanged gray-scale, without using the method of the present invention, and using the method of the present invention, and Figure 3 shown is the comparison of the visualization effects with and without using the brightness uniformity technology. It can be seen from the figure that using the present invention can reduce the sudden change of the gray mean value in the image sequence, effectively stabilize the thermal radiation bias field, and at the same time have good gray-scale retention with the original image.

[0079] The present invention provides a technology for brightness uniformity of the aerodynamic thermal radiation effect image sequence. Its overall concept is to deeply analyze the generation mechanism of related problems. Based on the analysis results, global constraints are added to the polynomial fitting coefficient vector of the aerodynamic thermal radiation effect to avoid sudden changes in the bias field surface of adjacent frames caused by noise points in the coefficient vector, stably estimate the bias field sequence, and uniformize the gray-scale of the image sequence. Further, the gray-scale of the corrected image sequence is constrained to smooth the gray-scale transition, so that the gray-scale of the finally reconstructed image sequence is further uniformized.

[0080] Embodiment 2

[0081] An embodiment of the present invention provides a system for luminance uniformity of an aero-thermal radiation effect image sequence, including:

[0082] A weight function construction module, configured to construct a weight function of the bias field fitting coefficient vector based on the aero-thermal radiation effect bias field fitting coefficient vector of each frame of the degraded image sequence; wherein, the weight function is used to associate the bias field fitting coefficient vectors of an n-frame degraded image sequence;

[0083] A bias field sparse vector construction module, configured to construct a bias field sparse vector of each frame of the degraded image using the weight function:

[0084]

[0085] In the formula, a i ' represents the bias field sparse vector of the i-th frame of the degraded image X i , a j represents the bias field fitting coefficient vector of the j-th frame of the degraded image, and k j represents the weight function of the bias field fitting coefficient vector of the j-th frame of the degraded image;

[0086] A bias field fitting module, configured to fit the bias field of each frame of the degraded image: B i = Wa i ', where B i represents the bias field of the i-th frame of the degraded image X i , and W is the dictionary used to obtain the bias field fitting coefficient vector;

[0087] A first luminance uniformity module, configured to subtract the corresponding fitted bias field from each frame of the degraded image to obtain each frame of corrected image, so as to achieve luminance uniformity of the degraded image sequence.

[0088] As a preferred implementation manner, the weight function is:

[0089]

[0090] where a i represents the bias field fitting coefficient vector of the i-th frame of the degraded image X i , k i represents the weight function of the bias field fitting coefficient vector a i , and 1 represents the L1 norm.

[0091] As a further design of the present invention, it further includes:

[0092] A fitting function construction module, configured to construct a fitting function based on the gray distribution of the image sequence for each frame of the corrected image:

[0093]

[0094]

[0095] In the formula, g i represents the fitting function of the i-th frame corrected image Z i based on the gray-level distribution of the image sequence; k t represents the fitting coefficient; Z m (p, q) is the gray value of the corrected image Z m at (p, q), and Z t (p, q) is the gray value of the corrected image Z t at (p, q), where w and h respectively represent the width and height of each frame of the corrected image;

[0096] The second brightness equalization module is used to replace the mean value of the corresponding corrected image with the fitting function to obtain an updated corrected image, thereby further equalizing the brightness of the degraded image sequence.

[0097] For the specific implementation manners of each of the above modules, please refer to the corresponding descriptions in Embodiment 1, which will not be elaborated herein.

[0098] Embodiment 3

[0099] An embodiment of the present invention provides an electronic device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the method in the above Embodiment 1 are implemented.

[0100] The electronic device may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The so-called processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The memory can be used to store computer programs and / or modules. The processor realizes various functions of the electronic device by running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory.

[0101] The related technical solutions are the same as above and will not be elaborated herein.

[0102] Embodiment 4

[0103] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method in Embodiment 1 above are implemented.

[0104] Specifically, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0105] The related technical solutions are the same as above and will not be elaborated here.

[0106] Embodiment 5

[0107] An embodiment of the present application provides a computer program product, including a computer program. When the computer program runs on a computer, the computer is caused to execute the steps of the method in Embodiment 1 above.

[0108] The related technical solutions are the same as above and will not be elaborated here.

[0109] Those skilled in the art can easily understand that the above are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for brightness homogenization of a pneumatic thermal radiation effect image sequence, characterized in that, Comprising: Based on the bias field fitting coefficient vectors of each degraded image in the degraded image sequence, constructing a weight function for the bias field fitting coefficient vectors; wherein, the weight function is used to correlate the bias field fitting coefficient vectors of an n-frame degraded image sequence; Constructing the bias field sparse vectors of each degraded image with the weight function: where a i ' represents the sparse vector of the bias field of the i-th degraded image X i , a j represents the fitting coefficient vector of the bias field of the j-th degraded image, and k j represents the weight function of the fitting coefficient vector of the bias field of the j-th degraded image; Fitting the bias field of each frame of degraded image: B i = Wa i ', where B i represents the bias field of the i-th frame of degraded image X i , W is the dictionary used to obtain the fitting coefficient vector of the bias field; Subtracting the corresponding fitted bias field from each degraded image to obtain each corrected image, so as to achieve the brightness uniformity of the degraded image sequence.

2. The method for luminance uniformity of the pneumatic thermal radiation effect image sequence according to claim 1, wherein The weight function is: Among them, a i represents the bias field fitting coefficient vector of the i-th frame of degraded image X i , k i represents the weight function of the bias field fitting coefficient vector a i , and || ||1 represents the L1 norm.

3. The method for uniformizing the brightness of an image sequence of pneumatic thermal radiation effects according to claim 1, wherein Obtaining the bias field fitting coefficient vectors of each degraded image in the degraded image sequence includes: Adopting the polynomial fitting method of the pneumatic thermal radiation effect field to fit the bias field of each degraded image in the degraded image sequence, and obtaining the bias field fitting coefficient vectors of each degraded image due to the pneumatic thermal radiation effect.

4. The method for uniformizing the brightness of an image sequence of pneumatic thermal radiation effects according to any one of claims 1 to 3, characterized in that After obtaining the corrected image, it further includes: Constructing a fitting function based on the gray distribution of the image sequence for each corrected image: where g i represents the fitting function of the i-th frame corrected image Z i based on the gray-level distribution of the image sequence; k t represents the fitting coefficient; Z m (p, q) is the gray-level value of the corrected image Z m at (p, q), and Z t (p, q) is the gray-level value of the corrected image Z t at (p, q), where w and h respectively represent the width and height of each frame of the corrected image; Replacing the mean value of the corresponding corrected image with the fitting function to obtain an updated corrected image, so as to achieve the further brightness uniformity of the degraded image sequence.

5. A system for uniformizing the brightness of an image sequence of pneumatic thermal radiation effects, characterized in that, Comprising: A weight function construction module, configured to construct a weight function for the bias field fitting coefficient vectors based on the bias field fitting coefficient vectors of each degraded image in the degraded image sequence; wherein, the weight function is used to correlate the bias field fitting coefficient vectors of an n-frame degraded image sequence; A bias field sparse vector construction module, configured to construct the bias field sparse vectors of each degraded image with the weight function: where a i ' represents the sparse vector of the bias field of the i-th degraded image X i , a j represents the fitting coefficient vector of the bias field of the j-th degraded image, and k j represents the weight function of the fitting coefficient vector of the bias field of the j-th degraded image; Bias field fitting module, used to fit the bias field of each frame of degraded image: B i = Wa i ', where B i represents the bias field of the i-th frame of degraded image X i , W is the dictionary used to obtain the bias field fitting coefficient vector; A first brightness uniformity module, configured to subtract the corresponding fitted bias field from each degraded image to obtain each corrected image, so as to achieve the brightness uniformity of the degraded image sequence.

6. The pneumatic thermal radiation effect image sequence brightness homogenization system according to claim 5, wherein The weight function is: Among them, a i represents the bias field fitting coefficient vector of the i-th frame of degraded image X i , k i represents the weight function of the bias field fitting coefficient vector a i , and || ||1 represents the L1 norm.

7. The pneumatic thermal radiation effect image sequence brightness uniformity system according to claim 5 or 6, characterized in that, It further includes: A fitting function construction module, configured to construct a fitting function based on the gray distribution of the image sequence for each corrected image: where g i represents the fitting function of the i-th frame corrected image Z i based on the gray-scale distribution of the image sequence; k t represents the fitting coefficient; Z m (p, q) is the gray-scale value of the corrected image Z m at (p, q), and Z t (p, q) is the gray-scale value of the corrected image Z t at (p, q), where w and h respectively represent the width and height of each frame of the corrected image; A second brightness uniformity module, configured to replace the mean value of the corresponding corrected image with the fitting function to obtain an updated corrected image, so as to achieve the further brightness uniformity of the degraded image sequence.

8. An electronic device, characterized in that, Comprising a computer-readable storage medium and a processor; The computer-readable storage medium is used to store executable instructions; The processor is configured to read the executable instructions stored in the computer-readable storage medium and execute the method for brightness uniformity of the pneumatic thermal radiation effect image sequence according to any one of claims 1-4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method for brightness uniformity of the pneumatic thermal radiation effect image sequence according to any one of claims 1-4.

10. A computer program product, characterized in that, Comprising a computer program, when the computer program runs on a computer, it causes the computer to execute the method for brightness uniformity of the pneumatic thermal radiation effect image sequence according to any one of claims 1-4.

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