Infrared image non-uniformity vignetting correction method based on gradient prior

Abstract

The invention relates to the technical field of infrared image processing, in particular to an infrared image non-uniformity vignetting correction method based on gradient prior, which comprises the following steps: acquiring a uniformly radiated infrared noise image of a target imaging system, and acquiring a gradient trend of infrared non-uniformity vignetting based on the infrared noise image; obtaining a real-time infrared image of the target imaging system, and obtaining a real-time gradient operator and a real-time gradient trend of the real-time infrared image based on the gradient trend; constructing an objective function based on the gradient trend, the real-time gradient operator and the real-time gradient trend, and solving the objective function to obtain an optimal value of the real-time gradient operator; and obtaining an optimal real-time gradient trend based on the real-time gradient operator optimal value, and correcting the real-time infrared image by using the optimal real-time gradient trend to obtain a target infrared image after non-uniformity vignetting correction. By using the method provided by the invention, the correction of the infrared non-uniform vignetting can be better realized.

Description

Technical Field

[0001] The present invention relates to the technical field of infrared image processing, and in particular to an infrared image non-uniformity vignetting correction method based on gradient prior. Background Art

[0002] Infrared imaging systems are widely used in military and civilian fields, including remote sensing, astronomical imaging, automatic target recognition, and video surveillance. However, in uncooled long-wave infrared (LWIR) imaging systems, temperature fluctuations in lenses and other mechanical components may cause a smooth intensity bias field to appear in the output image. Especially when the infrared camera captures low-contrast scenes, this phenomenon is more significant. This non-uniformity intensity bias noise seriously affects the performance of infrared imaging systems. This non-uniformity noise is spatially continuous, has a low amplitude, and depends on temperature, and is called infrared non-uniformity vignetting according to its characteristics. Traditional non-uniformity correction (NUC) techniques are designed specifically for focal plane array (FPA) detectors and are difficult to effectively eliminate the fixed-direction noise caused by optical factors. Therefore, it is very necessary to study effective image processing methods to make up for the hardware defects of infrared detectors.

[0003] The first significant category is based on spatial filtering and spectral filtering, attempting to remove the drastic changes in the image, thereby generating a smoothly varying intensity deviation. Filter-based methods have an inherent drawback. That is, it is difficult to appropriately select a threshold in both the spatial domain and the spectral domain to distinguish the intensity changes between the potential infrared image and the intensity deviation. The second main method is based on intensity or gradient domain fitting, using a function model to build the pseudo-contrast in the intensity domain. Another method is to learn the derivative and intensity deviation of the differential ideal infrared image. The third category attempts to solve infrared non-uniformity vignetting in the variational framework. This method fully considers the significant features of the real degraded infrared image. The alternating minimization method is used to solve the non-convex energy function to estimate the intensity deviation and the potential image. However, all of these above methods have some common defects: (1) It is easy to affect the real signal, resulting in the loss of the real signal; (2) The convergence speed is slow and the ghosting is serious; (3) It depends on the change of the scene and the information of the front and back frames. Therefore, it is of great significance to study a method for low-cost implementation of infrared image non-uniformity vignetting correction. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems in the related art to some extent.

[0005] To this end, the first object of the present invention is to propose an infrared image non-uniformity vignetting correction method based on gradient prior to better realize the correction of infrared non-uniformity vignetting.

[0006] The second object of the present invention is to propose an infrared image non-uniformity vignetting correction system based on gradient prior.

[0007] The third object of the present invention is to provide an electronic device.

[0008] The fourth object of the present invention is to provide a computer-readable storage medium.

[0009] To achieve the above object, the first aspect of the present invention provides a method for correcting non-uniform vignetting of an infrared image based on a gradient prior, including: Obtaining an infrared noise image of uniform radiation of a target imaging system, and obtaining a gradient trend of infrared non-uniform vignetting based on the infrared noise image; Obtaining a real-time infrared image of the target imaging system, and obtaining a real-time gradient operator and a real-time gradient trend of the real-time infrared image based on the gradient trend; Constructing an objective function based on the gradient trend, the real-time gradient operator and the real-time gradient trend, and solving the objective function to obtain an optimal value of the real-time gradient operator; Obtaining an optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and correcting the real-time infrared image by using the optimal real-time gradient trend to obtain a target infrared image after correcting non-uniform vignetting.

[0010] In the method of the first aspect of the present invention, the obtaining a gradient trend of infrared non-uniform vignetting based on the infrared noise image includes: performing polynomial surface fitting on the infrared noise image to obtain a gradient direction and a gradient operator of the infrared noise image, and obtaining the gradient trend of the infrared non-uniform vignetting based on the gradient direction and the gradient operator.

[0011] In the method of the first aspect of the present invention, the constructing an objective function based on the gradient trend, the real-time gradient operator and the real-time gradient trend includes: constructing an objective function based on the gradient trend, the real-time gradient operator and the real-time gradient trend in a manner of a standard least squares problem.

[0012] In the method of the first aspect of the present invention, the constructed objective function further includes a bias field smoothing prior term.

[0013] In the method of the first aspect of the present invention, solving the objective function is performed by using a ridge regression estimation method.

[0014] In the method of the first aspect of the present invention, after obtaining the infrared noise image, it is also necessary to preprocess the infrared noise image, and obtain a gradient trend of infrared non-uniform vignetting by using the preprocessed infrared noise image.

[0015] In the method of the first aspect of the present invention, the infrared noise image of uniform radiation refers to an image obtained by using the target imaging system to take a picture when the lens of the target imaging system is completely covered.

[0016] To achieve the above object, a second aspect of the present invention proposes an infrared image non-uniformity vignetting correction system based on gradient prior, including: A first acquisition module, configured to acquire an infrared noise image of uniform radiation of a target imaging system, and obtain a gradient trend of infrared non-uniformity vignetting based on the infrared noise image; A second acquisition module, configured to acquire a real-time infrared image of the target imaging system, and obtain a real-time gradient operator and a real-time gradient trend of the real-time infrared image based on the gradient trend; A processing module, configured to construct an objective function based on the gradient trend, the real-time gradient operator, and the real-time gradient trend, and solve the objective function to obtain an optimal value of the real-time gradient operator; A vignetting correction module, configured to obtain an optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and use the optimal real-time gradient trend to correct the real-time infrared image to obtain a target infrared image after non-uniformity vignetting correction.

[0017] To achieve the above object, a third aspect of the present invention proposes an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method proposed in the first aspect of the present invention.

[0018] To achieve the above object, a fourth aspect of the present invention proposes a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the method proposed in the first aspect of the present invention.

[0019] The infrared image non-uniformity vignetting correction method, system, electronic device and storage medium based on gradient prior provided by the present invention obtain an infrared noise image of uniform radiation of a target imaging system, and obtain the gradient trend of infrared non-uniformity vignetting based on the infrared noise image; obtain a real-time infrared image of the target imaging system, and obtain a real-time gradient operator and a real-time gradient trend of the real-time infrared image based on the gradient trend; construct an objective function based on the gradient trend, the real-time gradient operator and the real-time gradient trend, and solve the objective function to obtain the optimal value of the real-time gradient operator; obtain the optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and use the optimal real-time gradient trend to correct the real-time infrared image to obtain the target infrared image after non-uniformity vignetting correction. In this case, the infrared noise image of uniform radiation of the target imaging system is used to identify the gradient trend of non-uniformity vignetting generated by the target imaging system, and the gradient trend is used as a prior to obtain the optimal value of the real-time gradient operator of the real-time infrared image, and then obtain the optimal real-time gradient trend. Finally, the optimal real-time gradient trend is used to correct the real-time infrared image to obtain the target infrared image after non-uniformity vignetting correction. Compared with the real-time infrared image, the target infrared image eliminates the deviation and can more accurately restore the gray-scale distribution of the real scene, so the correction of infrared non-uniformity vignetting is better realized.

[0020] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. Description of the Drawings

[0021] The above and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, in which: Figure 1 is a schematic flow chart of an infrared image non-uniformity vignetting correction method based on gradient prior provided by an embodiment of the present invention; Figure 2 is a schematic diagram of the infrared vignetting trend of different infrared imaging systems provided by an embodiment of the present invention; Figure 3 is a schematic diagram of the gradient trend of different infrared imaging systems provided by an embodiment of the present invention; Figure 4 is a diagram of the infrared non-uniformity vignetting correction results of different infrared imaging systems provided by an embodiment of the present invention; Figure 5 is a block diagram of an infrared image non-uniformity vignetting correction system based on gradient prior provided by an embodiment of the present invention. Detailed Embodiments

[0022] Embodiments of the present invention will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where like or similar reference numerals denote like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present invention, and should not be construed as limiting the present invention.

[0023] The method and system for infrared image non-uniformity vignetting correction based on gradient prior according to the embodiments of the present invention will be described below with reference to the accompanying drawings.

[0024] The embodiments of the present invention provide a method for infrared image non-uniformity vignetting correction based on gradient prior to better realize the correction of infrared non-uniformity vignetting.

[0025] Figure 1 It is a schematic flow chart of a method for infrared image non-uniformity vignetting correction based on gradient prior provided by the embodiments of the present invention.

[0026] As Figure 1 shown, the method for infrared image non-uniformity vignetting correction based on gradient prior includes the following steps: Step S101, obtain an infrared noise image of uniform radiation of the target imaging system, and obtain the gradient trend of infrared non-uniformity vignetting based on the infrared noise image.

[0027] In step S101, the target imaging system refers to any infrared imaging system. The infrared noise image of uniform radiation refers to an image obtained by using the target imaging system when the lens of the target imaging system is completely covered.

[0028] It is easy to understand that the low-frequency non-uniform noise generated in the infrared imaging system mainly comes from the radiation attenuation of the optical system and the radiation interference of the core housing. The existence of this noise will significantly affect the imaging quality, resulting in an uneven brightness distribution in the image, and further affecting subsequent image processing and analysis. In the same imaging system, the characteristics of this non-uniform noise are mainly affected by the working environment of the detector. In addition, with the change of the environmental temperature and working time, the characteristics of the non-uniform noise will gradually evolve. For example, the increase in temperature may cause the thermal expansion of the optical elements, thereby changing the optical path and radiation characteristics of the optical system; while long-term work may lead to the performance decline of the detector, further aggravating the influence of the non-uniform noise. For pixel , the obtained infrared thermal radiation can be expressed as: (1) where represents the thermal radiation of the scene, is the radiation attenuation of the optical system, is the thermal radiation generated by the camera housing. Therefore, infrared non-uniformity vignetting acts as an additive noise.

[0029] To avoid the influence of the real scene signal on the extraction of infrared non-uniformity vignetting, it is necessary to obtain an infrared noise image under uniform radiation. Previous methods relied on expensive blackbody devices, etc. In the present invention, a lens cap is used to cover the lens to obtain an infrared noise image under uniform radiation.

[0030] To avoid the influence of the real scene signal on the gradient trend of infrared non-uniformity vignetting, it is necessary to obtain an infrared noise image under uniform radiation. Previous methods relied on expensive blackbody devices, etc. In the present invention, a lens cap is used to cover the lens, and an infrared noise image under uniform radiation is obtained by using the target imaging system. In this case, covering the lens with a lens cap can effectively eliminate the influence of external environmental factors on the image quality, so that the obtained infrared noise image only reflects the characteristics of uniform radiation.

[0031] Figure 2 is a schematic diagram of the infrared vignetting trend of different infrared imaging systems provided by the embodiments of the present invention. As Figure 2 shown, the first row shows the infrared noise image obtained under the infrared imaging system (a) and the corresponding infrared vignetting trend. The second row shows the infrared noise image obtained under the infrared imaging system (b) and the corresponding infrared vignetting trend. As Figure 2 shown, the infrared vignetting trends of different imaging systems vary greatly.

[0032] In step S101, after obtaining the infrared noise image, it is also necessary to preprocess the infrared noise image, and use the preprocessed infrared noise image to obtain the gradient trend of infrared non-uniformity vignetting. The preprocessing can be low-pass filtering. The preprocessed infrared noise image is a vignetting plan view. Specifically, the infrared noise image is processed by a low-pass filter to remove high-frequency noise and unnecessary details, and retain the low-frequency non-uniformity vignetting noise, so as to highlight the vignetting characteristics in the image.

[0033] In step S101, obtaining the gradient trend of infrared non-uniformity vignetting based on the infrared noise image includes: performing polynomial surface fitting on the infrared noise image to obtain the gradient direction and gradient operator of the infrared noise image, and obtaining the gradient trend of infrared non-uniformity vignetting based on the gradient direction and gradient operator.

[0034] Specifically, Figure 3 is a schematic diagram of the gradient trend of different infrared imaging systems provided by the embodiments of the present invention. Among them, Figure 3 in (a) is a schematic diagram of the gradient trend under an infrared imaging system, Figure 3Among them, (b) is a schematic diagram of the gradient trend under another infrared imaging system. Among them, G u represents the gradient trend under the corresponding infrared imaging system. U xy represents the gradient operator under the corresponding infrared imaging system. represents the gradient direction under the corresponding infrared imaging system. As Figure 3 shown, for different infrared imaging systems, different gradient trends are used to characterize the trend of intensity deviation.

[0035] For the target imaging system, if the non-uniform vignetting of the infrared noise image is vignetting from the center outwards, then polynomial surface fitting is used to obtain the corresponding noise center, analyze the change trend, and thus obtain the gradient direction. The gradient direction satisfies: (2) In the formula, represents the center of the non-uniform noise under uniform radiation, represents the coordinates of any pixel, represents a very small value to avoid division by 0. T represents the transpose. The gradient operator along the row / column of the preprocessed infrared noise image satisfies: (3) Combining the gradient operator and the gradient direction to characterize the vignetting gradient trend of the image, the gradient trend satisfies: (4) In the formula, represents the gradient trend of the infrared non-uniform vignetting of the target imaging system. This gradient trend reflects the non-uniformity performance of the target imaging system in infrared imaging.

[0036] Step S102, obtain the real-time infrared image of the target imaging system, and obtain the real-time gradient operator and real-time gradient trend of the real-time infrared image based on the gradient trend.

[0037] In step S102, the real-time infrared image can be an image captured in any case where the lens of the target imaging system is covered or uncovered.

[0038] Since the real-time infrared image includes non-uniform vignetting B , referring to the gradient trend in step S101, obtain the real-time gradient operator and real-time gradient trend of the non-uniform vignetting B in the real-time infrared image.

[0039] The real-time gradient trend satisfies: (5) (6) Wherein, is the real-time gradient trend of non-uniform vignetting B . is the real-time gradient operator of non-uniform vignetting B . Among them is affected by infrared radiation. is the gradient direction.

[0040] Step S103: Construct an objective function based on the gradient trend, real-time gradient operator and real-time gradient trend, and solve the objective function to obtain the optimal value of the real-time gradient operator.

[0041] In step S103, constructing an objective function based on the gradient trend, real-time gradient operator and real-time gradient trend includes: constructing an objective function in the manner of a standard least squares problem based on the gradient trend, real-time gradient operator and real-time gradient trend. The constructed objective function also includes a bias field smoothing prior term. Solving the objective function uses the ridge regression estimation method.

[0042] Specifically, considering the gradient representation forms in steps S101 and S102, the lower the thermal radiation in the real scene, the smaller the influence of the real-time infrared image on the intensity bias. Therefore, the objective of the present invention is to find minimum value. However, the low-frequency non-uniform noise has smoothness. To constrain the smoothness, a bias field smoothing prior is introduced into the objective function. Among them, is the second derivative of the real-time infrared image along the gradient direction . At the same time, in order to avoid overcorrecting the image like other existing methods and to make the obtained value have a unique solution, the present invention also adds a constraint on . Finally, the problem to be solved is simplified to a standard least squares problem to obtain the objective function, and the objective function satisfies: (7) Wherein, is the objective function, is the bias field smoothing prior term, is set to 2, is set to a very small value, such as 0.0001. represents the direction along . The meaning of the objective function is to minimize the difference between the non-uniformity in the image and the real scene.

[0043] Since the least squares problem here is irreversible or ill-conditioned, to ensure stability and reliability, the ridge regression estimation method is used for the objective function Solve to obtain the estimated . The estimated is the optimal value of the real-time gradient operator.

[0044] Step S104: Obtain the optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and use the optimal real-time gradient trend to correct the real-time infrared image to obtain the target infrared image after non-uniformity vignetting correction.

[0045] In step S104, since vignetting is additive noise, subtracting the estimated value from the real-time infrared image can achieve the correction of non-uniformity vignetting. Specifically, substitute the optimal value of the real-time gradient operator into equation (5) to obtain the optimal real-time gradient trend, which is the actual non-uniformity vignetting of the real-time infrared image. Subtracting the optimal real-time gradient trend from the real-time infrared image can obtain the target infrared image after non-uniformity vignetting correction.

[0046] Figure 4 This is the infrared non-uniformity vignetting correction result diagram of different infrared imaging systems provided by the embodiments of the present invention. As Figure 4 shown, the first row successively shows the real-time infrared image and the corresponding target infrared image obtained under the infrared imaging system (a). The second row successively shows the real-time infrared image and the corresponding target infrared image obtained under the infrared imaging system (b).

[0047] To implement the above embodiments, the present invention also proposes an infrared image non-uniformity vignetting correction system based on gradient prior.

[0048] Figure 5 This is the block diagram of an infrared image non-uniformity vignetting correction system based on gradient prior provided by the embodiments of the present invention.

[0049] As Figure 5 shown, the infrared image non-uniformity vignetting correction system based on gradient prior includes a first acquisition module 11, a second acquisition module 12, a processing module 13, and a vignetting correction module 14, where: The first acquisition module 11 is used to acquire the infrared noise image of uniform radiation of the target imaging system, and obtain the gradient trend of infrared non-uniformity vignetting based on the infrared noise image; The second acquisition module 12 is used to acquire the real-time infrared image of the target imaging system, and obtain the real-time gradient operator and real-time gradient trend of the real-time infrared image based on the gradient trend; The processing module 13 is used to construct an objective function based on the gradient trend, real-time gradient operator, and real-time gradient trend, and solve the objective function to obtain the optimal value of the real-time gradient operator; The vignetting correction module 14 is configured to obtain an optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and correct the real-time infrared image by using the optimal real-time gradient trend to obtain a target infrared image after non-uniform vignetting correction.

[0050] Further, in a possible implementation manner of the embodiment of the present invention, the infrared noise image with uniform radiation in the first acquisition module 11 refers to an image obtained by using the target imaging system when the lens of the target imaging system is completely covered.

[0051] Further, in a possible implementation manner of the embodiment of the present invention, in the first acquisition module 11, after the infrared noise image is acquired, it is also necessary to preprocess the infrared noise image, and obtain the gradient trend of the infrared non-uniform vignetting by using the preprocessed infrared noise image.

[0052] Further, in a possible implementation manner of the embodiment of the present invention, in the first acquisition module 11, obtaining the gradient trend of the infrared non-uniform vignetting based on the infrared noise image includes: performing polynomial surface fitting on the infrared noise image to obtain the gradient direction and the gradient operator of the infrared noise image, and obtaining the gradient trend of the infrared non-uniform vignetting based on the gradient direction and the gradient operator.

[0053] Further, in a possible implementation manner of the embodiment of the present invention, in the processing module 13, constructing the objective function based on the gradient trend, the real-time gradient operator, and the real-time gradient trend includes: constructing the objective function based on the gradient trend, the real-time gradient operator, and the real-time gradient trend in the manner of a standard least squares problem.

[0054] Further, in a possible implementation manner of the embodiment of the present invention, the objective function constructed in the processing module 13 further includes a bias field smoothing prior term.

[0055] Further, in a possible implementation manner of the embodiment of the present invention, the processing module 13 solves the objective function by using the ridge regression estimation method.

[0056] It should be noted that the foregoing explanation of the embodiment of the method for correcting non-uniform vignetting of an infrared image based on a gradient prior is also applicable to the system for correcting non-uniform vignetting of an infrared image based on a gradient prior in this embodiment, and will not be elaborated herein.

[0057] In an embodiment of the present invention, by acquiring an infrared noise image with uniform radiation of a target imaging system, the gradient trend of infrared non-uniformity vignetting is obtained based on the infrared noise image; a real-time infrared image of the target imaging system is acquired, and a real-time gradient operator and a real-time gradient trend of the real-time infrared image are obtained based on the gradient trend; a target function is constructed based on the gradient trend, the real-time gradient operator, and the real-time gradient trend, and the target function is solved to obtain the optimal value of the real-time gradient operator; an optimal real-time gradient trend is obtained based on the optimal value of the real-time gradient operator, and the real-time infrared image is corrected using the optimal real-time gradient trend to obtain a target infrared image after non-uniformity vignetting correction. In this case, the infrared noise image with uniform radiation of the target imaging system is used to identify the gradient trend of non-uniformity vignetting generated by the target imaging system, and the gradient trend is used as a prior to obtain the optimal value of the real-time gradient operator of the real-time infrared image, thereby obtaining the optimal real-time gradient trend. Finally, the real-time infrared image is corrected using the optimal real-time gradient trend to obtain a target infrared image after non-uniformity vignetting correction. Compared with the real-time infrared image, the target infrared image eliminates the deviation and can more accurately restore the gray-scale distribution of the real scene, so the correction of infrared non-uniformity vignetting is better realized.

[0058] The method and system of the present invention belong to the technical field of infrared image non-uniformity correction. Images captured under uniform radiation conditions are used to identify the trend of intensity deviation generated by each system, and various definitions of image gradients are designed as priors to help identify and eliminate the deviation. The enhanced image can accurately restore the gray-scale distribution of the real scene. By constructing a gradient prior function using the pre-known trend of infrared non-uniformity vignetting, the correction of infrared non-uniformity vignetting is realized based on the gradient prior. The problem that the non-uniformity vignetting noise caused by temperature fluctuations of lenses and other mechanical components in infrared imaging seriously affects the performance of infrared imaging systems is solved, and the correction of infrared non-uniformity vignetting is realized by establishing a gradient prior using the vignetting trend. The low-cost correction of infrared image non-uniformity vignetting can be achieved.

[0059] To implement the above embodiment, the present invention also provides an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided in the foregoing embodiment. To implement the above embodiment, the present invention also provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the method provided in the foregoing embodiment when executed by a processor.

[0060] To implement the above embodiment, the present invention also provides a computer program product including a computer program, which implements the method provided in the foregoing embodiment when executed by a processor.

[0061] In the description of the foregoing embodiments, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0062] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0063] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present invention includes additional implementations, where the functions may be performed in a substantially simultaneous manner or in the reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0064] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection parts with one or more wirings (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber devices, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other appropriate processing as necessary, and then storing it in a computer memory.

[0065] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.

[0066] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0067] In addition, each functional unit in various embodiments of the present invention may be integrated into a processing module, may exist separately physically for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0068] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. An infrared image non-uniformity vignetting correction method based on gradient prior, characterized in that, Including: Obtain an infrared noise image with uniform radiation of the target imaging system, and obtain the gradient trend of infrared non-uniformity vignetting based on the infrared noise image; Obtain a real-time infrared image of the target imaging system, and obtain the real-time gradient operator and real-time gradient trend of the real-time infrared image based on the gradient trend; Construct an objective function based on the gradient trend, real-time gradient operator and real-time gradient trend, and solve the objective function to obtain the optimal value of the real-time gradient operator; Obtain the optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and use the optimal real-time gradient trend to correct the real-time infrared image to obtain the target infrared image after non-uniformity vignetting correction.

2. The method for infrared image non-uniformity vignetting correction based on gradient prior according to claim 1, wherein The obtaining the gradient trend of infrared non-uniformity vignetting based on the infrared noise image includes: Perform polynomial surface fitting on the infrared noise image to obtain the gradient direction and gradient operator of the infrared noise image, and obtain the gradient trend of infrared non-uniformity vignetting based on the gradient direction and gradient operator.

3. The method for infrared image non-uniformity vignetting correction based on gradient prior according to claim 1, wherein The constructing an objective function based on the gradient trend, real-time gradient operator and real-time gradient trend includes: Construct an objective function based on the gradient trend, real-time gradient operator and real-time gradient trend in the manner of a standard least squares problem.

4. The method for infrared image non-uniformity vignetting correction based on gradient prior according to claim 1 or 3, characterized in that The constructed objective function further includes a bias field smoothing prior term.

5. The non-uniformity vignetting correction method for infrared images based on gradient prior according to claim 1, wherein Solving the objective function is by using the ridge regression estimation method.

6. The method for infrared image non-uniformity vignetting correction based on gradient prior according to claim 1, characterized in that After obtaining the infrared noise image, it is also necessary to preprocess the infrared noise image, and obtain the gradient trend of infrared non-uniformity vignetting by using the preprocessed infrared noise image.

7. The method for infrared image non-uniformity vignetting correction based on gradient prior according to claim 1, characterized in that The infrared noise image with uniform radiation refers to the image obtained by using the target imaging system when the lens of the target imaging system is completely covered.

8. An infrared image non-uniformity vignetting correction system based on gradient prior, characterized in that, Including: A first acquisition module, configured to acquire an infrared noise image with uniform radiation of the target imaging system, and obtain the gradient trend of infrared non-uniformity vignetting based on the infrared noise image; A second acquisition module, configured to acquire a real-time infrared image of the target imaging system, and obtain the real-time gradient operator and real-time gradient trend of the real-time infrared image based on the gradient trend; A processing module, configured to construct an objective function based on the gradient trend, real-time gradient operator and real-time gradient trend, and solve the objective function to obtain the optimal value of the real-time gradient operator; A vignetting correction module, configured to obtain the optimal real-time gradient trend based on the optimal value of the real-time gradient operator, and use the optimal real-time gradient trend to correct the real-time infrared image to obtain the target infrared image after non-uniformity vignetting correction.

9. An electronic device, characterized in that, Including: A processor, and a memory communicatively connected to the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, Computer execution instructions are stored in the computer-readable storage medium, and when the computer execution instructions are executed by a processor, they are used to implement the method according to any one of claims 1-7.

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