An image enhancement method, device, and storage medium

Abstract

The present application provides an image enhancement method, apparatus, and computer storage medium. The method includes: obtaining Chebyshev bases of each pixel point in the image to be processed; performing an indefinite integral operation on each of the Chebyshev bases to obtain a first indefinite integral value; enhancing the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain an enhanced image of the image to be processed. Through the above manner, the effect of image enhancement is achieved in the image to which the Chebyshev decomposition method is applied.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and particularly to an image enhancement method, apparatus, and storage medium. Background Art

[0002] When an image sensor acquires an image, there are various problems such as unremarkable details and a blurred image, which are not conducive to subsequent scientific research and also affect people's visual experience. Therefore, as an important branch of image processing, image enhancement has continuously attracted the attention of many scientific workers at home and abroad.

[0003] Existing image enhancement algorithms can be roughly divided into statistical-based image enhancement algorithms, layer-based image enhancement methods, and learning-based image enhancement algorithms. Statistical-based image enhancement algorithms mainly include classic algorithms such as global histogram enhancement method, local histogram enhancement method, and CLAHE. Layer-based image enhancement methods mainly include the Retinex method and methods that use filtering or equation optimization to extract high frequencies for enhancement. And learning-based image enhancement algorithms mainly include sparse coding methods and the relatively rapidly developing deep learning methods in recent years. The problems existing in the current prior art are: for backlit human faces in the highlight area, the enhancement effect is poor. And the prior art does not involve a technical solution for image enhancement using Chebyshev decomposition. Summary of the Invention

[0004] To solve the above technical problems, this application proposes an image enhancement method, apparatus, and computer storage medium.

[0005] To solve the above technical problems, this application proposes an image enhancement method, the image enhancement method comprising: obtaining Chebyshev bases of each pixel point in the image to be processed; performing an indefinite integral operation on each of the Chebyshev bases to obtain a first indefinite integral value; enhancing the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain an enhanced image of the image to be processed.

[0006] Wherein, the enhancing the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain an enhanced image of the image to be processed comprises: scaling the Chebyshev bases of each pixel point to obtain a first scaling result; performing a weighted calculation on the first indefinite integral value and the first scaling result to obtain a weighted pixel value; generating the enhanced image based on the weighted pixel value.

[0007] After scaling the Chebyshev basis of each pixel point to obtain a first scaling result, the image enhancement method further includes: performing mean filtering on the first scaling result to obtain a second scaling result; the step of calculating a weighted pixel value by weighting the first indefinite integral value and the first scaling result includes: calculating a weighted pixel value by weighting the first indefinite integral value and the second scaling result; generating the enhanced image based on the weighted pixel value.

[0008] Before obtaining the Chebyshev basis of each pixel point in the image to be processed, the image enhancement method further includes: obtaining the number of bits of the image to be processed and the original pixel value of each pixel point; performing interval mapping on the original pixel value based on the number of bits of the image to obtain the mapped pixel value of each pixel point.

[0009] The step of scaling the Chebyshev basis of each pixel point to obtain a first scaling result includes: scaling the Chebyshev basis based on the square of the Chebyshev basis of each pixel point and the mapped pixel value to obtain the first scaling result.

[0010] The step of generating the enhanced image based on the weighted pixel value includes: obtaining the number of bits of the image to be processed;

[0011] mapping the weighted pixel value to the pixel value numerical range of the image to be processed based on the number of bits of the image to obtain a mapped weighted pixel value; updating the original pixel value of the pixel point in the image to be processed with the mapped weighted pixel value to generate the enhanced image.

[0012] The step of updating the original pixel value of the pixel point in the image to be processed with the mapped weighted pixel value to generate the enhanced image includes: performing weighted accumulation on the mapped weighted pixel value and the original pixel value of the same pixel point according to a preset weight to obtain an enhanced pixel value; obtaining the final enhanced image according to the enhanced pixel value.

[0013] The step of performing an indefinite integral operation on each Chebyshev basis to obtain a first indefinite integral value includes: obtaining the indefinite integral operation formula of each Chebyshev basis; expanding the indefinite integral operation formula to obtain a preset number of groups of indefinite integral operation sub-formulas, where the indefinite integral operation sub-formula is constructed by the recurrence relation of the Chebyshev basis; calculating the first indefinite integral value by jointly using the preset number of groups of indefinite integral operation sub-formulas.

[0014] To solve the above technical problems, the present application also proposes an image enhancement device, including an enhancer and a memory connected to the enhancer. The memory stores program instructions, and the enhancer executes the program instructions to implement the above image enhancement method.

[0015] To solve the above technical problems, the present application also proposes a computer-readable storage medium storing program instructions, and when the program instructions can be executed by an enhancer, the above image enhancement method is implemented.

[0016] Compared with the prior art, the beneficial effects of the present application are as follows: obtaining Chebyshev bases of each pixel point in the image to be processed; performing indefinite integral operations on each of the Chebyshev bases to obtain first indefinite integral values; enhancing corresponding pixel points based on the first indefinite integral values corresponding to each pixel point to obtain an enhanced image of the image to be processed. In the above manner, the Chebyshev decomposition method is applied to the image to achieve the effect of image enhancement. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Among them:

[0019] Figure 1 is a schematic flowchart of the first embodiment of the image enhancement method provided by the present application;

[0020] Figure 2 is a schematic flowchart of the second embodiment of the image enhancement method provided by the present application;

[0021] Figure 3 is a schematic flowchart of the sub-steps of step S12 of the image enhancement method proposed by the present application;

[0022] Figure 4 is a schematic flowchart of the third embodiment of the image enhancement method provided by the present application;

[0023] Figure 5 is a weighted schematic flowchart of the image enhancement method provided by the present application;

[0024] Figure 6 is a schematic flowchart of the sub-steps of step S33 in the image enhancement method provided by the present application;

[0025] Figure 7 is a schematic structural diagram of an embodiment of the image enhancement device provided by the present application;

[0026] Figure 8 It is a schematic structural diagram of an embodiment of the computer storage medium provided by the present application. Specific embodiments

[0027] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0028] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned accompanying drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application described here, for example, can be implemented in an order other than those illustrated or described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] Specifically, please refer to Figure 1 、 Figure 1 It is a schematic flowchart of the first embodiment of the image enhancement method provided by the present application.

[0030] The image enhancement method of the present application is applied to an image enhancement device. Among them, the image enhancement device of the present application can be a server, a local terminal, or a system in which the server and the local terminal cooperate with each other. Correspondingly, each part included in the image enhancement device, such as each unit, subunit, module, and submodule, can be all set in the server, all set in the local terminal, or respectively set in the server and the local terminal.

[0031] Furthermore, the above-mentioned server can be hardware or software. When the server is hardware, it can be implemented as a distributed server cluster composed of multiple servers or as a single server. When the server is software, it can be implemented as multiple software or software modules, such as software or software modules used to provide a distributed server, or as a single software or software module, which is not specifically limited here.

[0032] As Figure 1 shown, the specific steps are as follows:

[0033] Step S11: Obtain the Chebyshev basis of each pixel point in the image to be processed.

[0034] Specifically, according to the Chebyshev decomposition principle, the image enhancement device substitutes the pixel value of each pixel point in the image to be processed into the Chebyshev recurrence formula to obtain the Chebyshev basis of each pixel point in the image to be processed as shown in the figure.

[0035] It should be noted that when using the Chebyshev decomposition principle, the input data must satisfy the interval [-1, 1]. Therefore, it is necessary to perform interval mapping on the pixel values of the image to obtain the mapped image I im , substituting the image after interval mapping into the above formula, multiple Chebyshev bases T m (I im ) can be calculated.

[0036] An embodiment of the present application is proposed to perform interval mapping on the pixel values of the image so that the pixel values of the image meet the basic requirements of the Chebyshev decomposition principle. For details, please refer to Figure 2 , Figure 2 which is a schematic flowchart of the second embodiment of the image enhancement method provided by the present application.

[0037] As Figure 2 shown, the specific steps are as follows:

[0038] Step S21: Obtain the number of bits of the image to be processed and the original pixel value of each pixel point.

[0039] Specifically, generally in an image chip, the most frequently used number of bits for the image bit width is 8, 10, 12. The image enhancement device calculates to obtain the number of bits (bit width) of the image to be processed and obtains the original pixel value I of each pixel point in the image to be processed.

[0040] Step S22: Perform interval mapping on the original pixel value based on the number of bits of the image to obtain the mapped pixel value of each pixel point.

[0041] Since the pixel ranges of images with different numbers of bits are different, in the embodiment of the present application, for an X-bit grayscale image, the method of interval mapping is

[0042] Generally in an image chip, the most frequently used number of bits for the image bit width is 8, 10, 12. Therefore, the specific formula for interval mapping can be expressed as:

[0043]

[0044]

[0045]

[0046] Through the above pixel value mapping process, the pixel range of the image to be processed can meet the requirements of using the Chebyshev principle.

[0047] Step S12: Perform indefinite integral operations on each Chebyshev basis to obtain the first indefinite integral value.

[0048] Specifically, the image processing device performs indefinite integral operations on the Chebyshev basis of each pixel point in each image to be processed to obtain the first indefinite integral value INT. The specific formula is as follows:

[0049]

[0050] Among them, m is the number of Chebyshev bases. For example, if 7 pixel points are enhanced, m is 6, and the image enhancement device calculates 7 groups of INT, namely INT0, INT1, INT2, INT3, INT4, INT5, and INT6.

[0051] In other embodiments of the present application, m can also start from other values. For example: m = 1, which is not limited in the present application.

[0052] In order to further achieve the technical effect of simplifying operations, the present application proposes steps S121 - S123 as sub - steps of step S12. For details, please refer to Figure 3 , Figure 3 is a schematic flowchart of the sub - steps of step S12 of the image enhancement method proposed in the present application.

[0053] As Figure 3 shown, the specific steps are as follows:

[0054] Step S121: Obtain the indefinite integral operation formula for each Chebyshev basis.

[0055] Specifically, the image enhancement device obtains the indefinite integral operation formula for each Chebyshev basis.

[0056] Step S122: Expand the indefinite integral operation formula to obtain a preset number of sub - formulas for indefinite integral operations.

[0057] Among them, the sub - formula for indefinite integral operation is constructed from the recurrence relation of the Chebyshev basis.

[0058] Specifically, expand and substitute the Chebyshev recurrence formula for the part containing the Chebyshev basis in the expansion part to obtain the final indefinite integral value.

[0059] Step S123: Use the preset number of sub - formulas for indefinite integral operations to jointly calculate the first indefinite integral value.

[0060] The specific formula is expressed as:

[0061] INT0(I im ) = T0(I im ) + T1(I im )

[0062]

[0063]

[0064]

[0065]

[0066]

[0067]

[0068] Calculate T0(I im ), T1(I im ), T2(I im ), T3(I im ), T4(I im ), T5(I im ), T6(I im ) and T7(I im ) using the Chebyshev recurrence formula.

[0069] Using the above formula, the indefinite integral value of the Chebyshev basis T of the pixel points can be obtained.

[0070] Among them, in the embodiments of the present application, the series of the Chebyshev basis is the number of Chebyshev bases of a preset number of pixel points, which is obtained according to the actual situation, and the present application does not limit the number.

[0071] In the present application, through the first indefinite integral value INT calculation formula of the Chebyshev basis, the combination of T is used to obtain the first indefinite integral value INT of the Chebyshev basis. Since T can be obtained by the Chebyshev recurrence formula, the huge operation logic required for calculating the indefinite integral can be effectively avoided.

[0072] At the same time, therefore, the image enhancement method proposed in the present application can save computing resources. The more levels are divided, the better the effect. Even some low-cost chips can use the indefinite integral of the Chebyshev basis with lower levels to improve the operation efficiency and save costs.

[0073] In the above manner, by adopting the Chebyshev decomposition principle, since the Chebyshev basis can be calculated using a recurrence formula, and the indefinite integral of the Chebyshev basis can be obtained by combining the Chebyshev basis after being simplified in this patent, the operation logic is greatly reduced. This makes the image enhancement method proposed in this application very suitable for integration into an image chip. By adopting the Chebyshev decomposition principle and performing Chebyshev decomposition on each pixel point, the enhanced image will not have the problem of sudden contrast change. Moreover, the more levels of decomposition, the more obvious the improvement of the sudden change situation.

[0074] Step S13: Enhance the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain the enhanced image of the image to be processed.

[0075] Specifically, the image enhancement device enhances the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain the enhanced image of the image to be processed.

[0076] In the embodiment of this application, in order to improve the image enhancement effect, it also includes a process of performing mean filtering with pixel value scaling on the Chebyshev basis, as Figure 4 and Figure 5 shown. Figure 4 is a schematic flowchart of the third embodiment of the image enhancement method provided by this application; Figure 5 is a schematic weighted flowchart of the image enhancement method provided by this application.

[0077] As Figure 4 shown, the specific steps are as follows:

[0078] Step S31: Scale the Chebyshev basis of each pixel point to obtain the first scaling result.

[0079] In an embodiment of this application, scaling the Chebyshev basis of the first pixel point includes the first scaling result obtained by pixel value scaling and mean filtering.

[0080] In this embodiment, based on the square of the Chebyshev basis of each pixel point and the mapped pixel value, perform pixel value scaling on the Chebyshev basis to obtain the first scaling result. The specific formula is as follows:

[0081]

[0082] In the embodiment of this application, scaling the Chebyshev basis of the first pixel point also includes the first scaling result obtained by respectively using pixel value scaling and mean filtering scaling.

[0083] First, it is necessary to perform pixel value scaling on the Chebyshev basis. The formula is expressed as follows:

[0084]

[0085] Then perform mean filtering on TS m (I im ) as follows:

[0086] TSM m (I im ) = Mean Ω (TS m (I im ))

[0087] Combining the two formulas can be expressed as:

[0088]

[0089] Among them, Ω represents the range of mean filtering, and this parameter is used to control the locality of image enhancement. The larger Ω is, the more the image enhancement tends to global enhancement. The smaller Ω is, the more the image enhancement tends to local enhancement. The larger Ω is, the less likely black and white edges appear. The smaller Ω is, the more various texture details of the image are highlighted after enhancement.

[0090] In other embodiments of the present application, scaling the Chebyshev basis of the first pixel point includes that the image enhancement device can also perform pixel value scaling on the Chebyshev basis and the first scaling result obtained by any filtering method.

[0091] In other embodiments of the present application, it also includes any other image scaling method that can achieve the image enhancement effect.

[0092] Through the above method, the image enhancement effect can be further improved.

[0093] Step S32: Perform weighted calculation on the first indefinite integral value and the first scaling result to obtain a weighted pixel value.

[0094] As Figure 5 shown, after the image enhancement device performs interval mapping on the image pixels, it obtains multiple Chebyshev bases, performs indefinite integral operation on the Chebyshev bases to obtain the first indefinite integral value INT m , performs mean filtering with pixel value scaling on the Chebyshev bases to obtain the first scaling result TSM m , and weights the first indefinite integral value INT m of a preset number in the image to be processed with the first scaling result TSM m to obtain the weighted pixel value Res.

[0095] The specific formula is as follows:

[0096]

[0097] Among them, the first scaling result TSM mIt can be any one of the first scaling results in the embodiments of the present application. For example, the first scaling result can be the first scaling result obtained by any scaling method capable of achieving an image enhancement effect, and the first scaling result can also be the first scaling result obtained by the image enhancement device scaling the pixel values of the Chebyshev basis. It can also be the first scaling result obtained by the image enhancement device scaling the pixel values of the Chebyshev basis and any filtering method, or the first scaling result obtained by the image enhancement device performing mean filtering with pixel value scaling on the Chebyshev basis.

[0098] Step S33: Generate an enhanced image based on the weighted pixel values.

[0099] Specifically, the image enhancement device generates an enhanced image according to the weighted pixel value Res.

[0100] Furthermore, the present application proposes steps S331 - S333 as sub-steps of step S33 for performing image inverse mapping. For details, please refer to Figure 6 , Figure 6 which is a schematic flowchart of the sub-steps of step S33 in the image enhancement method provided by the present application.

[0101] As Figure 6 shown, the specific steps are as follows:

[0102] Step S331: Obtain the number of bits of the image to be processed.

[0103] Specifically, the image enhancement device calculates to obtain the number of bits of the image to be processed.

[0104] Step S332: Map the weighted pixel values to the pixel value numerical range of the image to be processed based on the number of bits of the image to obtain the mapped weighted pixel values.

[0105] The image enhancement device maps the numerical range of Res to be the same as the numerical range of the input image I to obtain the mapped weighted pixel value Res'.

[0106] Res′ = Res × (2 X -1).

[0107] When the bit width bit number of the input image is 8, 10, or 12, the specific formula for interval inverse mapping can be expressed as:

[0108] Res′ = Res × 255

[0109] Res′ = Res × 1023

[0110] Res′ = Res × 4095

[0111] Step S333: Update the original pixel value of the pixel points in the image to be processed by using the mapped weighted pixel value, and generate an enhanced image.

[0112] Specifically, in an embodiment of the present application, according to a preset weight, the image enhancement device performs weighted accumulation on the mapped weighted pixel value and the original pixel value of the same pixel point to obtain an enhanced pixel value. The image enhancement device further obtains the final enhanced image according to the enhanced pixel value. The specific formula is as follows:

[0113] Ide = I × α + Res′ × (1.0 - α).

[0114] Wherein, α is used to control the intensity of image enhancement, and the range of α is [0, 1]. The larger α is, the more the final image Ide tends to the original image I, and the weaker the enhancement intensity is. The smaller α is, the more the final image Ide tends to, and the stronger the enhancement intensity is.

[0115] In the embodiment of the present application, α is a custom parameter, which can be adjusted according to the usage scenario, so as to achieve the corresponding image enhancement effect. Through the above method, the degree of image enhancement can be adaptively adjusted.

[0116] The present application uses the recurrence formula of Chebyshev decomposition to construct the multi-level Chebyshev basis of the image, adopts the indefinite integral calculation method given in the patent to obtain the indefinite integral value of the Chebyshev basis, and finally realizes the image enhancement effect through weighted combination, pixel value inverse mapping and enhancement intensity adjustment. Using the method of combining Chebyshev bases to obtain the indefinite integral value of the Chebyshev basis, this method avoids directly calculating the indefinite integral, reduces the amount of calculation, and integrating the algorithm into the chip is beneficial to reducing the chip power consumption and cost.

[0117] To implement the above image enhancement method, the present application also proposes an image enhancement device. For details, please refer to Figure 7 , Figure 7 is a schematic structural diagram of an embodiment of the image enhancement device provided by the present application.

[0118] The image enhancement device 400 in this embodiment includes a processor 41, a memory 42, an input / output device 43, and a bus 44.

[0119] The processor 41, the memory 42, and the input / output device 43 are respectively connected to the bus 44. The memory 42 stores program data, and the processor 41 is used to execute the program data to implement the image enhancement method described in the above embodiment.

[0120] In an embodiment of the present application, the processor 41 may also be referred to as a CPU (Central Processing Unit). The processor 41 may be an integrated circuit chip with signal processing capabilities. The processor 41 may also be a general-purpose processor, a digital signal processor (DSP, Digital Signal Process), an application specific integrated circuit (ASIC, Application Specific Integrated Circuit), a field programmable gate array (FPGA, Field Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor 41 may also be any conventional processor, etc.

[0121] The present application also provides a computer storage medium. Please continue to refer to Figure 8 , Figure 8 FIG. is a schematic structural diagram of an embodiment of the computer storage medium provided by the present application. A computer program 61 is stored in the computer storage medium 600. When the computer program 61 is executed by a processor, it is used to implement the image enhancement method in the above embodiment.

[0122] When the embodiments of the present application are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods described in various embodiments of the present application. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0123] The above are only the embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structural or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

Claims

1. An image enhancement method, characterized in that, The described image enhancement method includes: Obtaining the Chebyshev basis of each pixel point in the image to be processed; Performing an indefinite integral operation on each of the Chebyshev bases to obtain a first indefinite integral value; Enhancing the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain an enhanced image of the image to be processed; The enhancing the corresponding pixel points based on the first indefinite integral value corresponding to each pixel point to obtain an enhanced image of the image to be processed includes: Scaling the Chebyshev basis of each pixel point to obtain a first scaling result; Performing mean filtering on the first scaling result to obtain a second scaling result; Performing a weighted calculation on the first indefinite integral value and the second scaling result to obtain a weighted pixel value; Generating the enhanced image based on the weighted pixel value.

2. The image enhancement method according to claim 1, wherein Before obtaining the Chebyshev basis of each pixel point in the image to be processed, the image enhancement method further includes: Obtaining the number of bits of the image to be processed and the original pixel value of each pixel point; Performing interval mapping on the original pixel value based on the number of bits of the image to obtain the mapped pixel value of each pixel point.

3. The image enhancement method according to claim 1, wherein The scaling the Chebyshev basis of each pixel point to obtain a first scaling result includes: Scaling the Chebyshev basis based on the Chebyshev basis of each pixel point and the square of the mapped pixel value to obtain the first scaling result.

4. The image enhancement method according to claim 1, wherein The generating the enhanced image based on the weighted pixel value includes: Obtaining the number of bits of the image to be processed; Mapping the weighted pixel value to the pixel value numerical range of the image to be processed based on the number of bits of the image to obtain a mapped weighted pixel value; Updating the original pixel value of the pixel points in the image to be processed with the mapped weighted pixel value to generate the enhanced image.

5. The image enhancement method according to claim 4, wherein The updating the original pixel value of the pixel points in the image to be processed with the mapped weighted pixel value to generate the enhanced image includes: Performing weighted accumulation on the mapped weighted pixel value and the original pixel value of the same pixel point according to a preset weight to obtain an enhanced pixel value; Obtaining the final enhanced image according to the enhanced pixel value.

6. The image enhancement method according to claim 1, wherein The performing an indefinite integral operation on each of the Chebyshev bases to obtain a first indefinite integral value includes: Obtaining the indefinite integral operation formula of each of the Chebyshev bases; Expanding the indefinite integral operation formula to obtain a preset number of groups of indefinite integral operation sub-formulas, wherein the indefinite integral operation sub-formulas are constructed by the recurrence relation of the Chebyshev basis; Jointly calculating the first indefinite integral value by using the preset number of groups of indefinite integral operation sub-formulas.

7. An image enhancement device, characterized in that, It includes an intensifier and a memory connected to the intensifier. The memory stores program instructions, and the intensifier executes the program instructions to implement the image enhancement method according to any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, There are program instructions stored, and when the program instructions can be executed by the intensifier, the image enhancement method according to any one of claims 1-6 can be implemented.

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