Irradiance image denoising method and system based on adaptive median filtering

Abstract

The present application relates to a kind of based on adaptive median filtering irradiation image denoising method and system, comprising the following steps: obtaining irradiation image;Irradiation image is analyzed, obtains the noise degradation characteristics of irradiation image;Adaptive median filtering after pixel value is calculated;According to the pixel value after adaptive median filtering, denoising is handled, obtains the recovery effect diagram of irradiation image.The present application can effectively solve the noise degradation problem of irradiation image of radiation-hardened camera, obtains ideal recovery effect, has very good filtering effect to the noise point of random particle size and random density distribution existing in irradiation image in radiation environment, simultaneously, while removing noise, the original detail information in irradiation image is as far as possible preserved.

Description

Technical Field

[0001] This invention relates to the field of irradiation image processing, and more specifically, to an irradiation image denoising method and system based on adaptive median filtering. Background Technology

[0002] Irradiation environments are highly radioactive, which can cause performance degradation in electronic components such as sensors. During the acquisition, conversion, and transmission of images, the acquired image information may contain some random, discrete, or isolated image noise due to the influence of both the hardware system itself and the external irradiation environment.

[0003] Currently, a common approach is to use image processing algorithms to eliminate the effects of non-uniform illumination. Commonly used methods include histogram equalization, the Retinex algorithm, and algorithms based on deep total area neural networks.

[0004] The above methods, especially the implementation of complex algorithms, all use high-performance processors and ported image processing libraries. Although the processing effect is good, the hardware cannot meet the usage requirements of the irradiated area, and the failure rate is extremely high. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and system for denoising irradiated images based on adaptive median filtering, which addresses the shortcomings of the prior art.

[0006] The technical solution adopted by this invention to solve its technical problem is: constructing an irradiation image denoising method based on adaptive median filtering, comprising the following steps:

[0007] Acquire irradiation images;

[0008] The irradiation image is analyzed to obtain its noise degradation characteristics;

[0009] Calculate the pixel values ​​after adaptive median filtering;

[0010] The denoising process is performed on the pixel values ​​after adaptive median filtering to obtain the restored image of the irradiated image.

[0011] In the irradiation image denoising method based on adaptive median filtering described in this invention, obtaining the irradiation image includes:

[0012] Filming irradiation videos;

[0013] The irradiation video is cropped to obtain the irradiation image.

[0014] In the irradiation image denoising method based on adaptive median filtering described in this invention, the step of analyzing the irradiation image to obtain the noise degradation features of the irradiation image includes:

[0015] The probability density distribution of noise in the irradiated image is statistically analyzed;

[0016] Based on the probability density distribution results, the noise degradation characteristics of the irradiated image are obtained.

[0017] In the irradiation image denoising method based on adaptive median filtering described in this invention, the step of calculating the pixel value after adaptive median filtering according to the noise degradation characteristics includes:

[0018] Initialize the filter;

[0019] Calculate the current size of the filter;

[0020] Determine whether the current size of the filter is greater than the threshold.

[0021] If so, output the pixel value after adaptive median filtering;

[0022] If not, calculate the grayscale value of the irradiated image based on the filter, and perform adaptive median filtering based on the grayscale value of the irradiated image.

[0023] In the irradiation image denoising method based on adaptive median filtering described in this invention, the initialization of the filter includes:

[0024] The grayscale value at the region coordinates of the irradiated image within the filter region is represented as the region grayscale value;

[0025] Determine the initial size of the filter and position the center point of the filter at the region coordinates of the irradiated image;

[0026] Determine the maximum size of the filter.

[0027] In the irradiation image denoising method based on adaptive median filtering described in this invention, the gray values ​​of the irradiation image include: minimum gray value, maximum gray value, and median gray value.

[0028] The step of calculating the grayscale value of the irradiated image based on the filter and performing adaptive median filtering based on the grayscale value of the irradiated image includes:

[0029] The minimum gray value, the maximum gray value, and the median gray value of the irradiated image are calculated based on the filter.

[0030] The minimum grayscale value, the maximum grayscale value, and the median grayscale value are compared and judged, and adaptive median filtering is performed based on the comparison and judgment results.

[0031] In the irradiation image denoising method based on adaptive median filtering described in this invention, the step of comparing and judging the magnitudes of the minimum gray value, the maximum gray value, and the median gray value, and performing adaptive median filtering processing based on the comparison and judgment results includes:

[0032] Determine whether the minimum grayscale value, the median grayscale value, and the maximum grayscale value satisfy the first condition;

[0033] If so, determine whether the minimum gray value, the gray value of the region, and the maximum gray value satisfy the second condition;

[0034] If the minimum gray value, the gray value of the region, and the maximum gray value satisfy the second condition, then the gray value of the region is determined to be the pixel value after adaptive median filtering and output; otherwise, the median gray value is determined to be the pixel value after adaptive median filtering and output.

[0035] In the irradiation image denoising method based on adaptive median filtering described in this invention, the method further includes:

[0036] If the minimum grayscale value, the median grayscale value, and the maximum grayscale value do not meet the first condition, then the size of the filter is increased and the calculation is repeated.

[0037] In the irradiation image denoising method based on adaptive median filtering described in this invention, the first condition is:

[0038] The minimum grayscale value is less than the median grayscale value, and the median grayscale value is less than the maximum grayscale value;

[0039] The second condition is: the minimum gray value is less than the gray value of the region, and the gray value of the region is less than the maximum gray value.

[0040] The present invention also provides an irradiation image denoising system based on adaptive median filtering, comprising:

[0041] Acquisition unit, used to acquire irradiation images;

[0042] An analysis unit is used to analyze the irradiation image to obtain the noise degradation characteristics of the irradiation image;

[0043] The calculation unit is used to calculate the pixel value after adaptive median filtering;

[0044] The denoising unit is used to perform denoising processing based on the pixel values ​​after adaptive median filtering to obtain the restored image of the irradiated image.

[0045] The radiation image denoising method and system based on adaptive median filtering of the present invention has the following beneficial effects: It includes the following steps: acquiring an radiation image; analyzing the radiation image to obtain its noise degradation characteristics; calculating the pixel values ​​after adaptive median filtering; and performing denoising processing based on the pixel values ​​after adaptive median filtering to obtain a restored image of the radiation image. This invention can effectively solve the noise degradation problem of radiation-hardened camera images, achieving ideal restoration results. It has a good filtering effect on noise points with random particle size and density distribution in radiation images under radiation conditions. Simultaneously, while removing noise, it preserves as much of the original detail information in the radiation image as possible. Attached Figure Description

[0046] The present invention will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings:

[0047] Figure 1 This is a flowchart illustrating the irradiation image denoising method based on adaptive median filtering provided in an embodiment of the present invention.

[0048] Figure 2 This is a schematic diagram of the adaptive median filtering process provided in an embodiment of the present invention;

[0049] Figure 3 This is a schematic diagram of the structure of the irradiation image denoising system based on adaptive median filtering provided in an embodiment of the present invention. Detailed Implementation

[0050] To provide a clearer understanding of the technical features, objectives, and effects of the present invention, specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0051] The purpose of this invention is to provide an irradiation image denoising method based on adaptive median filtering, which can be applied in irradiation environments to solve the problem of image noise degradation caused by irradiation in current radiation-hardened camera equipment.

[0052] For details, please refer to Figure 1 This is a flowchart illustrating an optional embodiment of the irradiation image denoising method based on adaptive median filtering provided by the present invention.

[0053] like Figure 1 As shown, the irradiation image denoising method based on adaptive median filtering includes the following steps:

[0054] Step S101: Obtain the irradiation image.

[0055] Optionally, in this embodiment of the invention, obtaining an irradiation image includes: capturing an irradiation video; and cropping an image from the irradiation video to obtain an irradiation image.

[0056] Specifically, a radiation-hardened camera is fixed in front of a radiation source, with the center of the radiation source and the camera coaxial. The camera collects radiation video, and an radiation image is obtained by cropping the captured video. The cropping method can be any existing conventional method, and this invention is not specifically limited to it.

[0057] Step S102: Analyze the irradiation image to obtain the noise degradation characteristics of the irradiation image.

[0058] Optionally, in this embodiment of the invention, analyzing the irradiation image to obtain its noise degradation features includes: statistically analyzing the probability density distribution of noise in the irradiation image; and obtaining the noise degradation features of the irradiation image based on the probability density distribution results. Here, the noise degradation features mainly refer to noise being the bright spots with the highest grayscale values ​​distributed in the image.

[0059] Specifically, by analyzing irradiation images, noise degradation features can be obtained. These noise degradation features resemble "salt and pepper noise," and their probability density function is expressed as follows:

[0060]

[0061] Here, a and b both represent grayscale values. We can assume b > a; grayscale value b will appear as a bright spot in the image, and grayscale value a will appear as a dark spot. a p represents the probability that the gray value of any pixel z in the irradiated image is a. b This represents the probability that any pixel z in the irradiated image has a gray value of b. The "salt-and-pepper noise" in the irradiated image only manifests as bright spots with a gray value of b. That is, b represents the brightest spot with the highest gray value distributed throughout the irradiated image.

[0062] Step S103: Calculate the pixel values ​​after adaptive median filtering.

[0063] Optionally, in this embodiment of the invention, calculating the pixel value after adaptive median filtering includes:

[0064] Step S1031: Initialize the filter.

[0065] Optionally, in this embodiment of the invention, initializing the filter includes: representing the grayscale value at the region coordinates of the irradiated image within the filter region as the region grayscale value; determining the initial size of the filter and locating the center point of the filter at the region coordinates of the irradiated image; and determining the maximum size of the filter.

[0066] Specifically, let the filter be W. xy The region coordinates are (x, y), and the region grayscale value is F. xySpecifically, in filter W xy The gray value at the region coordinates (x, y) of the irradiated image within the region is represented by the region gray value F. xy Select filter W xy The initial size is n0×n0, the center point is located at the region coordinates (x, y) of the irradiated image, and the filter W is set. xy The maximum size is N×N.

[0067] Step S1032: Calculate the current size of the filter.

[0068] Optionally, in this embodiment of the invention, after completing filter W... xy After initialization, based on the initialized filter W xy Calculate the filter W during the i-th cycle. xy The size, i.e., n i ×n i , where n i =n i-1 +2 (n≥1).

[0069] Step S1033: Determine whether the current size of the filter is greater than the threshold.

[0070] Specifically, step S1031 shows that the maximum size of the filter is N×N, therefore, the threshold can be set to N×N. Thus, determining whether the current size of the filter is greater than the threshold can be done by adjusting the n calculated in step S1032. i Compare with N. That is, determine n. i Is it greater than N?

[0071] Step S1034: If yes, output the pixel value after adaptive median filtering.

[0072] Specifically, if n i If the value is greater than N, then the pixel value after adaptive median filtering is determined to be F. xy And output; if n i If the value is less than or equal to N, then proceed to step S1035.

[0073] Step S1035: If not, calculate the gray value of the irradiated image according to the filter, and perform adaptive median filtering processing based on the gray value of the irradiated image.

[0074] Optionally, in this embodiment of the invention, the grayscale values ​​of the irradiated image include: minimum grayscale value, maximum grayscale value, and median grayscale value.

[0075] In some embodiments, calculating the grayscale value of the irradiated image based on the filter and performing adaptive median filtering based on the grayscale value of the irradiated image includes: calculating the minimum grayscale value, the maximum grayscale value, and the median grayscale value of the irradiated image based on the filter; comparing and judging the magnitudes of the minimum grayscale value, the maximum grayscale value, and the median grayscale value, and performing adaptive median filtering based on the comparison and judgment results.

[0076] The process of comparing and judging the minimum, maximum, and median gray values, and then performing adaptive median filtering based on the comparison results, includes: determining whether the minimum, median, and maximum gray values ​​satisfy a first condition; if so, determining whether the minimum, region gray values, and maximum gray values ​​satisfy a second condition; if the minimum, region gray values, and maximum gray values ​​satisfy the second condition, then determining the region gray value as the pixel value after adaptive median filtering and outputting it; otherwise, determining the median gray value as the pixel value after adaptive median filtering and outputting it.

[0077] Furthermore, if the minimum, median, and maximum grayscale values ​​do not meet the first condition, the filter size is increased and the calculation is repeated.

[0078] Optionally, in this embodiment of the invention, the first condition is: the minimum grayscale value is less than the median grayscale value, and the median grayscale value is less than the maximum grayscale value; the second condition is: the minimum grayscale value is less than the grayscale value of the region, and the grayscale value of the region is less than the maximum grayscale value.

[0079] Specifically, if n i If N is less than or equal to N, then the calculation is performed on filter W. xy Minimum gray value F of the irradiated image within the region min Maximum grayscale value F max and grayscale median F mid Next, determine F. min F max and F mid The size of F; if F min <F mid <F max Then determine F min F max and F xy If the size is not specified, proceed to step S1032 to increase filter W. xy The dimensions are recalculated, and execution continues. If F min <F xy <F max Then the pixel value after adaptive median filtering is determined to be F. xy And output; otherwise, determine the pixel value after adaptive median filtering as F. mid And output it.

[0080] The specific process of adaptive median filtering is as follows: Figure 2 As shown. The specific steps are as follows:

[0081] Step S201: Initialize the filter.

[0082] Step S202: Calculate the filter size n i .

[0083] Step S203, determine n i Is it less than or equal to N (i.e., n)? i Is it greater than N?

[0084] Step S204, if n i If the value is greater than N, then output F. xy .

[0085] Step S205, if n i If N is less than or equal to N, then calculate F. min F max and F mid .

[0086] Step S206: Determine whether F is satisfied. min <F mid <F max If not, return to step S202 to increase the size and recalculate.

[0087] Step S207: If yes, determine whether F is satisfied. min <F xy <F max If not, output F xy .

[0088] Step S208: If yes, output F. mid .

[0089] Step S104: Perform denoising processing based on the pixel values ​​after adaptive median filtering to obtain the restored image of the irradiated image.

[0090] Specifically, in this embodiment of the invention, after obtaining the noise degradation characteristics in the irradiation image through statistical analysis, median filtering is used to eliminate bright spots. Specifically, the filter iterates through each pixel in the irradiation image. First, it determines whether the median value within the filter's coverage area is appropriate. Then, it determines whether the current center point is a bright spot within the filter's area. If not, the original grayscale value is retained; if the center point is determined to be noise, the grayscale value at the noise bright spot is replaced with the median value within the filter's area, thereby eliminating noise and obtaining the restored irradiation image.

[0091] The present invention also provides an irradiation image denoising system based on adaptive median filtering. This irradiation image denoising system based on adaptive median filtering can be used to implement the irradiation image denoising method based on adaptive median filtering disclosed in the embodiments of the present invention.

[0092] Specifically, such as Figure 3 As shown, the irradiation image denoising system based on adaptive median filtering includes:

[0093] Acquisition unit 301 is used to acquire irradiation images.

[0094] Specifically, a radiation-hardened camera is fixed in front of a radiation source, with the center of the radiation source and the camera coaxial. The camera collects radiation video, and an radiation image is obtained by cropping the captured video. The cropping method can be any existing conventional method, and this invention is not specifically limited to it.

[0095] Analysis unit 302 is used to analyze the irradiation image and obtain the noise degradation characteristics of the irradiation image.

[0096] Optionally, in this embodiment of the invention, analyzing the irradiation image to obtain its noise degradation features includes: statistically analyzing the probability density distribution of noise in the irradiation image; and obtaining the noise degradation features of the irradiation image based on the probability density distribution results. Here, the noise degradation features mainly refer to noise being the bright spots with the highest grayscale values ​​distributed in the image.

[0097] Specifically, by analyzing irradiation images, noise degradation features can be obtained. These noise degradation features resemble "salt and pepper noise," and their probability density function is expressed as follows:

[0098]

[0099] Here, a and b both represent grayscale values. We can assume b > a; grayscale value b will appear as a bright spot in the image, and grayscale value a will appear as a dark spot. a p represents the probability that the gray value of any pixel z in the irradiated image is a. b This represents the probability that any pixel z in the irradiated image has a gray value of b. The "salt-and-pepper noise" in the irradiated image only manifests as bright spots with a gray value of b. That is, b represents the brightest spot with the highest gray value distributed throughout the irradiated image.

[0100] The calculation unit 303 is used to calculate the pixel value after adaptive median filtering.

[0101] Specifically, in this embodiment of the invention, the calculation unit 303 is specifically used to: initialize the filter; calculate the current size of the filter; determine whether the current size of the filter is greater than a threshold; if yes, output the pixel value after adaptive median filtering; if no, calculate the gray value of the irradiated image according to the filter, and perform adaptive median filtering processing according to the gray value of the irradiated image.

[0102] Optionally, in this embodiment of the invention, initializing the filter includes: representing the grayscale value at the region coordinates of the irradiated image within the filter region as the region grayscale value; determining the initial size of the filter and locating the center point of the filter at the region coordinates of the irradiated image; and determining the maximum size of the filter.

[0103] Specifically, let the filter be W. xy The region coordinates are (x, y), and the region grayscale value is F. xy Specifically, in filter W xy The gray value at the region coordinates (x, y) of the irradiated image within the region is represented by the region gray value F. xy Select filter W xy The initial size is n0×n0, the center point is located at the region coordinates (x, y) of the irradiated image, and the filter W is set. xy The maximum size is N×N.

[0104] After completing filter W xy After initialization, based on the initialized filter W xy Calculate the filter W during the i-th cycle. xy The size, i.e., n i ×n i , where n i =n i-1 +2 (n≥1). Specifically, as mentioned above, the maximum size of the filter is N×N, therefore, the threshold can be set to N×N. Thus, determining whether the current size of the filter is greater than the threshold can be done by using the n calculated in step S1032. i Compare with N. That is, determine n. i Is it greater than N?

[0105] Specifically, if n i If the value is greater than N, then the pixel value after adaptive median filtering is determined to be F. xy And output; if n i If the grayscale value is less than or equal to N, then the grayscale value of the irradiated image is calculated according to the filter, and adaptive median filtering is performed based on the grayscale value of the irradiated image. Optionally, in this embodiment of the invention, the grayscale value of the irradiated image includes: minimum grayscale value, maximum grayscale value, and median grayscale value.

[0106] In some embodiments, calculating the grayscale value of the irradiated image based on the filter and performing adaptive median filtering based on the grayscale value of the irradiated image includes: calculating the minimum grayscale value, the maximum grayscale value, and the median grayscale value of the irradiated image based on the filter; comparing and judging the magnitudes of the minimum grayscale value, the maximum grayscale value, and the median grayscale value, and performing adaptive median filtering based on the comparison and judgment results.

[0107] The process of comparing and judging the minimum, maximum, and median gray values, and then performing adaptive median filtering based on the comparison results, includes: determining whether the minimum, median, and maximum gray values ​​satisfy a first condition; if so, determining whether the minimum, region gray values, and maximum gray values ​​satisfy a second condition; if the minimum, region gray values, and maximum gray values ​​satisfy the second condition, then determining the region gray value as the pixel value after adaptive median filtering and outputting it; otherwise, determining the median gray value as the pixel value after adaptive median filtering and outputting it.

[0108] Furthermore, if the minimum, median, and maximum grayscale values ​​do not meet the first condition, the filter size is increased and the calculation is repeated.

[0109] Optionally, in this embodiment of the invention, the first condition is: the minimum grayscale value is less than the median grayscale value, and the median grayscale value is less than the maximum grayscale value; the second condition is: the minimum grayscale value is less than the grayscale value of the region, and the grayscale value of the region is less than the maximum grayscale value.

[0110] Specifically, if n i If N is less than or equal to N, then the calculation is performed on filter W. xy Minimum gray value F of the irradiated image within the region min Maximum grayscale value F max and grayscale median F mid Next, determine F. min F max and F mid The size of F; if F min <F mid <F max Then determine F min F max and F xy The size of the filter W should be adjusted accordingly; otherwise, increase the filter W. xy The current size of the filter is recalculated based on the size of F, and execution continues. min <F xy <F max Then the pixel value after adaptive median filtering is determined to be F. xy And output; otherwise, determine the pixel value after adaptive median filtering as F. mid And output it.

[0111] The denoising unit 304 is used to perform denoising processing based on the pixel values ​​after adaptive median filtering to obtain the restored image of the irradiated image.

[0112] In this embodiment of the invention, after obtaining the noise degradation characteristics in the irradiation image through statistical analysis, median filtering is used to eliminate bright spots. Specifically, the filter iterates through each pixel in the irradiation image. First, it is determined whether the median value within the filter's coverage area is appropriate. Then, it is determined whether the current center point is a bright spot within the filter's coverage area. If not, the original grayscale value is retained. If the center point of the filter is determined to be noise, the grayscale value at the noisy bright spot is replaced with the median value within the filter's coverage area, thereby eliminating noise and obtaining the restored irradiation image.

[0113] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0114] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0115] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented directly by hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0116] The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement it accordingly. They do not limit the scope of protection of the present invention. All equivalent changes and modifications made within the scope of the claims of the present invention should fall within the scope of the claims of the present invention.

Claims

1. A method for denoising irradiated images based on adaptive median filtering, characterized in that, Includes the following steps: Acquire irradiation images; The irradiation image is analyzed to obtain its noise degradation characteristics; The analysis of the irradiated image to obtain its noise degradation features includes: statistically analyzing the probability density distribution of noise in the irradiated image; obtaining the noise degradation features of the irradiated image based on the probability density distribution results; the noise degradation features refer to the noise being bright spots with the largest gray values ​​distributed in the image; the probability density function of the noise degradation features is expressed as follows: ； in, a , b All represent grayscale values; assuming b > a grayscale value b Displayed as a bright spot in the image, grayscale value a It appears as a dark spot in the image; p a Represents any pixel in an irradiated image z grayscale value a The probability, p b Represents any pixel in an irradiated image z grayscale value b The probability; noise degradation features in irradiated images are only reflected in grayscale values. b The highlights, namely b The brightest point with the highest gray value in the irradiated image; Calculate the pixel value after adaptive median filtering; the calculation of the pixel value after adaptive median filtering includes: initializing the filter; calculating the current size of the filter; determining whether the current size of the filter is greater than a threshold; if yes, output the pixel value after adaptive median filtering; if no, calculate the gray value of the irradiated image according to the filter, and perform adaptive median filtering processing according to the gray value of the irradiated image. The denoising process is performed based on the pixel values ​​after adaptive median filtering and the noise degradation features to obtain the restored image of the irradiated image.

2. The irradiation image denoising method based on adaptive median filtering according to claim 1, characterized in that, The acquisition of the irradiation image includes: Filming irradiation videos; The irradiation video is cropped to obtain the irradiation image.

3. The irradiation image denoising method based on adaptive median filtering according to claim 1, characterized in that, The filter initialization includes: The grayscale value at the region coordinates of the irradiated image within the filter region is represented as the region grayscale value; Determine the initial size of the filter and position the center point of the filter at the region coordinates of the irradiated image; Determine the maximum size of the filter.

4. The irradiation image denoising method based on adaptive median filtering according to claim 3, characterized in that, The grayscale values ​​of the irradiated image include: minimum grayscale value, maximum grayscale value, and median grayscale value; The step of calculating the grayscale value of the irradiated image based on the filter and performing adaptive median filtering based on the grayscale value of the irradiated image includes: The minimum gray value, the maximum gray value, and the median gray value of the irradiated image are calculated based on the filter. The minimum grayscale value, the maximum grayscale value, and the median grayscale value are compared and judged, and adaptive median filtering is performed based on the comparison and judgment results.

5. The irradiation image denoising method based on adaptive median filtering according to claim 4, characterized in that, The step of comparing and judging based on the minimum gray value, the maximum gray value, and the median gray value, and performing adaptive median filtering based on the comparison and judgment results includes: Determine whether the minimum grayscale value, the median grayscale value, and the maximum grayscale value satisfy the first condition; If so, determine whether the minimum gray value, the gray value of the region, and the maximum gray value satisfy the second condition; If the minimum gray value, the gray value of the region, and the maximum gray value satisfy the second condition, then the gray value of the region is determined to be the pixel value after adaptive median filtering and output; otherwise, the median gray value is determined to be the pixel value after adaptive median filtering and output.

6. The irradiation image denoising method based on adaptive median filtering according to claim 5, characterized in that, The method further includes: If the minimum grayscale value, the median grayscale value, and the maximum grayscale value do not meet the first condition, then the size of the filter is increased and the calculation is repeated.

7. The irradiation image denoising method based on adaptive median filtering according to claim 6, characterized in that, The first condition is: The minimum grayscale value is less than the median grayscale value, and the median grayscale value is less than the maximum grayscale value; The second condition is: the minimum gray value is less than the gray value of the region, and the gray value of the region is less than the maximum gray value.

8. A radiation image denoising system based on adaptive median filtering, characterized in that, include: Acquisition unit, used to acquire irradiation images; An analysis unit is used to analyze the irradiation image to obtain the noise degradation characteristics of the irradiation image; The analysis of the irradiated image to obtain its noise degradation features includes: statistically analyzing the probability density distribution of noise in the irradiated image; obtaining the noise degradation features of the irradiated image based on the probability density distribution results; the noise degradation features refer to the noise being bright spots with the largest gray values ​​distributed in the image; the probability density function of the noise degradation features is expressed as follows: ； in, a , b All represent grayscale values; assuming b > a grayscale value b Displayed as a bright spot in the image, grayscale value a It appears as a dark spot in the image; p a Represents any pixel in an irradiated image z grayscale value a The probability, p b Represents any pixel in an irradiated image z grayscale value b The probability; noise degradation features in irradiated images are only reflected in grayscale values. b The highlights, namely b The brightest point with the highest gray value in the irradiated image; A calculation unit is used to calculate the pixel value after adaptive median filtering; the calculation of the pixel value after adaptive median filtering includes: initializing the filter; calculating the current size of the filter; determining whether the current size of the filter is greater than a threshold; if yes, outputting the pixel value after adaptive median filtering; if no, calculating the gray value of the irradiated image according to the filter, and performing adaptive median filtering processing according to the gray value of the irradiated image. The denoising unit is used to perform denoising processing based on the pixel values ​​after adaptive median filtering to obtain the restored image of the irradiated image.

Images