Rapid acquisition and quality enhancement method for high-temperature image of scanning electron microscope

Abstract

The invention discloses a scanning electron microscope high-temperature image rapid acquisition and quality enhancement method, which comprises the following steps: rapidly acquiring a scanning electron microscope image of a high-temperature heating sample to form an original image pixel value matrix; redistribution mapping is carried out on the obtained original image pixel value matrix, and preliminary brightness enhancement adjustment of the image is completed; calculating high and low thresholds of the image after brightness enhancement, and redistributing image pixel matrix values according to the high and low thresholds of the image to complete contrast enhancement adjustment of the image; establishing an optimal filtering window model of the image, updating the size of a window according to comparison and judgment of the optimal filtering window model and a self-defined variance threshold value, and balancing the requirements of the image for keeping details and removing noise; and combining a plurality of image processing results to synthesize a new image. According to the method, the problem of image distortion caused by the acquisition speed is effectively solved, the problems of image contrast imbalance and excessive noise are solved, and not only can the acquired image be processed in real time, but also the image can be displayed in real time.

Description

Technical Field

[0001] The invention belongs to the technical field of image processing, and in particular relates to a method for quickly collecting and enhancing the quality of high-temperature images of a scanning electron microscope. Background Art

[0002] In the field of aerospace material research, the metal materials of aircraft engines operate at hundreds or even thousands of degrees Celsius. In order to study the changes in the various microstructures of such materials, it is necessary to heat the samples in the vacuum chamber of the scanning electron microscope to conduct high-temperature in-situ experiments and capture the experimental phenomena to facilitate the next step of analysis and characterization. However, high-temperature imaging with scanning electron microscopes is still a major challenge in the study of high-temperature metal materials. Since some high-temperature experimental phenomena occur rapidly, the speed of scanning electron microscopes to acquire images is limited, which will cause data loss and image distortion. After the sample temperature rises to 800°C, due to the interference of thermal electrons, the scanned image will have corresponding contrast imbalance, gray or white images, and excessive noise.

[0003] Existing methods for image acquisition in high temperature experiments often manually assign parameters based on subjective judgment, which may result in insufficient or excessive adjustments, making the image too bright or too dark, and amplifying noise signals, making the image blurred.

[0004] In the field of materials science, high-temperature in-situ testing based on scanning electron microscopy is an important method for studying key information such as the sustainable use time and mechanical stability of alloy materials. When conducting observation experiments on samples, scanning electron microscopes generally use secondary electrons for imaging. However, when scanning electron microscopes conduct in-situ high-temperature tests, the surface of the material will undergo slight deformation due to the increase in temperature, and this deformation occurs rapidly. The scanning electron microscope has a limited image acquisition speed, which will cause the image to be distorted. Therefore, image information is acquired based on a fast image acquisition system to avoid image distortion problems. At the same time, since the secondary electron signal is affected by the thermal electrons released by the sample, the electron signal excited by the electron beam hitting the sample presents a periodic change of more or less, which is reflected in the image, manifested as an image contrast imbalance, the picture itself will appear gray or white, and the image will have problems such as excessive image noise, blurriness, and reduced quality. Summary of the invention

[0005] In order to overcome the deficiencies of the prior art, the present invention provides a method for rapid acquisition and quality enhancement of high-temperature images using a scanning electron microscope, which improves the image distortion and image quality degradation problems caused by acquisition using a scanning electron microscope during in-situ high-temperature testing.

[0006] The technical solution adopted by the present invention to solve the technical problem is: a method for rapid acquisition and quality enhancement of high-temperature images of a scanning electron microscope, comprising the following steps:

[0007] Rapidly collect SEM images of high-temperature heated samples to form a matrix of original image pixel values;

[0008] Redistribute and map the acquired original image pixel value matrix to complete the preliminary enhancement adjustment of the image brightness;

[0009] Calculate the high and low thresholds of the image after brightness enhancement, redistribute the image pixel matrix values ​​according to the high and low thresholds of the image, and complete the contrast enhancement adjustment of the image;

[0010] Establish the optimal window model for image filtering, update the window size based on the comparison and judgment with the custom variance threshold, and balance the need to retain image details and remove noise;

[0011] Combine multiple image processing results to synthesize a new image.

[0012] Furthermore, the heating temperature of the high-temperature heated sample is greater than or equal to 800° C., and the scanning electron microscope image acquisition speed of the high-temperature heated sample is 170ns / pixel to 320ns / pixel.

[0013] Furthermore, in the step of quickly acquiring the scanning electron microscope image of the high-temperature heated sample, an embedded high-temperature image rapid acquisition device is used to perform multiple line-by-line raster scanning acquisitions on the high-temperature heated sample.

[0014] Furthermore, the following steps are included: transmitting the collected image pixel value data to the host computer, the host computer starts the sub-thread and adds the collected image data to the sub-thread for processing, and finally displays the image processed by the sub-thread in real time on the main thread display interface of the host computer.

[0015] Furthermore, in the step of reallocating and mapping the acquired original image pixel value matrix,

[0016] Calculate each pixel value in the pixel matrix according to the following formula, and get the new pixel value to replace the original pixel value matrix:

[0017]

[0018] Among them, NewData represents the new pixel grayscale value after calculation;

[0019] Data represents the original pixel value at the current position;

[0020] DataMax represents the maximum pixel value present in the image matrix;

[0021] DataMin represents the minimum pixel value present in the image matrix;

[0022] Total represents the maximum grayscale distribution number of the image, which is calculated based on the number of bits of the image.

[0023] Furthermore, the step of calculating the high and low thresholds of the brightness enhanced image includes the following sub-steps: defining the low threshold with D min Indicates that D min The value determines the edge of the area with the lowest pixel value starting from 0 in the adjusted image;

[0024] Define the high threshold with D max Indicates that D max The value determines the edge of the area with the highest pixel value starting from the maximum grayscale value of the adjusted image;

[0025] Calculate the histogram of the image, starting from the pixel value 0, and accumulate the number of pixels in the histogram until the cumulative sum reaches or exceeds the total number of pixels in the image S for the first time. low , S low and S high is a percentage value, at this time, the cumulative number of pixels is greater than or equal to the total number of pixels S low The first pixel value is D min ;

[0026]

[0027] Count backward from the maximum value of the pixel in the image until the number of pixels is greater than or equal to the total number of pixels S high The first pixel value i of max ;

[0028]

[0029] Where total and total_pixel are the total number of pixels in the image;

[0030] Redistribute the image pixel matrix values ​​when the pixel value is less than D min All values ​​are assigned to 0. When the pixel value is in D min With D min Redistribution calculation is performed between them. When the pixel value is greater than D min The pixel value is set to the maximum grayscale according to the number of image bits;

[0031]

[0032] Until all pixels are adjusted, a new image pixel matrix is ​​generated.

[0033] Furthermore, the step of establishing the optimal window model for filtering the image, updating the window size based on the comparison and judgment with the custom variance threshold, and balancing the need to retain image details and remove noise includes the following sub-steps:

[0034] For the input image I and a window of size W×W, for each pixel (x, y) in the image, define the local variance σ 2 (x, y), the variance indicates the degree of change of the pixel value within the window;

[0035]

[0036] Where W is the size of the window, u(x, y) represents the mean value of the pixels in the window,

[0037]

[0038] For each window of size k×k, denoted as W k , Z xy Represents the pixel value at position (x, y) in image g, the minimum value Z in the window min , maximum value Z max and median Z med The calculation method is as follows,

[0039] Z xy =g(x, y);

[0040]

[0041] Z med =median({g(i,j)|(i,j)∈W k});

[0042] The first judgment, judgment Z med Does Z satisfy max >Z med >Z min If it satisfies, then Z med It is not salt and pepper noise, so keep the window and proceed to the second judgment;

[0043] The second judgment, judgment Z xy Does Z satisfy max >Z xy >Z min , if the current pixel Z xy Meet Z max >Z xy >Z min , then it means that Z xy It is not salt and pepper noise, so the original value is retained;

[0044] If the current pixel Z xy Not satisfied with Z max >Z xy >Z min , then use Z med Replace Z xy The value of

[0045] If Z med Not satisfied with Z max >Z med >Z min , you need to increase the window size until it reaches the preset maximum window size, and repeat the first judgment.

[0046] Furthermore, in the step of combining the processing results of multiple images to synthesize a new image, for a set of input images I i (x, y), where i represents the i-th frame image, (x, y) represents the pixel coordinates, and for the output image O(x, y), the pixel values ​​are determined by performing median calculation on the pixel values ​​at the same position of multiple images, and then a new image is synthesized, O(x, y) = median{I i (x, y)}.

[0047] Furthermore, in the step of combining the processing results of multiple images to synthesize a new image, for the output image S(x, y), the corresponding pixel value of the output image is generated by calculating the average value of all pixel values ​​of the corresponding pixel matrix positions of the multiple images, I i (x, y) is the pixel value at the same position in the i-th input image,

[0048] The beneficial effects of the present invention are as follows: after the in-situ high-temperature test reaches 800 degrees Celsius, the motion of thermal electrons on the sample surface caused by heating becomes more intense, and the thermal electrons are more easily excited, resulting in the imaging signal showing changes from time to time. At the same time, due to slight deformation of the sample surface, the scanned image causes image distortion, image contrast imbalance, excessive noise, and gray and white images. After quickly acquiring the test sample, the method effectively solves the image distortion problem caused by slight deformation of the sample surface, remaps and allocates the pixel grayscale values ​​in the image; calculates the high threshold and low threshold of the image pixel value and remaps and allocates the image pixel value according to the high and low thresholds; establishes the image filtering optimal window model; determines the filtering optimal window size and applies it; synthesizes multiple median or mean images, effectively solves the problems of poor contrast adjustment and noise amplification of high-temperature images, avoids the problem of unusable image data under high-temperature tests and difficulty in experimental data acquisition, and can not only process the quickly acquired images, but also process and display the images in real time; effectively solves the image distortion problem caused by the acquisition speed, solves the problem of image contrast imbalance and excessive noise, and can not only process the acquired images in real time, but also display the images in real time, avoiding the impact on experimental characterization and analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1These are images processed by the method of the present invention, wherein Figure a and Figure c show the pure nickel sample collected at 1000°C at a magnification of 2000 and 20000, respectively, which are the original images quickly collected and adjusted after the brightness enhancement step but not subjected to other processing, and Figure b and Figure d are the quality enhanced result images obtained after processing by this method. DETAILED DESCRIPTION

[0050] In order to enable those skilled in the art to better understand the solutions of the present invention, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0051] A method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope comprises the following steps:

[0052] Rapidly collect SEM images of high-temperature heated samples to form a matrix of original image pixel values;

[0053] Specifically, an embedded fast acquisition device is used to acquire a scanning electron microscope image, a sample with a melting point above 800°C is selected, a sample and a heater are installed, the experimental sample is placed in a scanning electron microscope chamber for heating, the heating temperature of the sample is set to be greater than 800°C, the sample is scanned using a scanning electron microscope, and the initial image data of the area to be observed is acquired at the scanning electron microscope acquisition end; the above steps are repeated, the experimental sample is raster-scanned from top to bottom line by line using a scanning electron microscope, and the scanned image is acquired rapidly and continuously for multiple times. Under the fast acquisition system, an embedded device is used to control the scanning electron microscope to acquire the experimental sample image, which can avoid image distortion caused by the scanning speed. Specifically, the acquired image pixel value data is transmitted to the host computer, the host computer starts the sub-thread and adds the acquired image data to the sub-thread for processing, and finally the image processed by the sub-thread is displayed in real time on the main thread display interface of the host computer.

[0054] In this embodiment, the embedded fast acquisition device includes an A / D converter chip and a D / A converter chip, which are responsible for processing the digital and analog conversion of the signal; a PCIE communication module, which is used to achieve high-speed data transmission; a Bessel signal filter, which optimizes the signal processing; a processor and a memory, wherein the memory is embedded with a program for controlling the acquisition of the original image data, and the processor is responsible for the execution of these programs; the host computer program runs on an independent computer, which is used to connect and control the above electronic equipment and implement this method. It can be implemented by the existing technology, and will not be repeated.

[0055] Since the surface of the material will undergo slight deformation at high temperatures, and this deformation occurs at a relatively fast speed, an embedded high-temperature image rapid acquisition device is used to perform three raster acquisitions on the high-temperature heated samples at an acquisition speed of 170ns / pixel to 320ns / pixel. The preferred acquisition speed is 180ns / pixel, which has a fast effect compared to the current scanning electron microscope image acquisition speed of 3.2us / pixel to 10us / pixel. The existing method takes 3.2S to acquire a 1K resolution image, and the method takes 1.4-1.5S to acquire a 1K resolution result image. This can avoid the problem of image distortion caused by high-temperature acquisition, create a matrix of the same size as the target result image, and perform raster acquisition row by row from the upper left corner to the lower right corner according to the raster filling method, fill the matrix pixel by pixel, and form an original image pixel value matrix.

[0056] The acquired original image pixel value matrix is ​​reassigned and mapped to complete the preliminary enhancement adjustment of the image brightness; for the pixel value at each position, the value is reassigned according to the distribution of the maximum pixel value and the minimum pixel value of the entire image, which can avoid the image being too dark or too bright as a whole;

[0057] The original secondary electron signal obtained by the acquisition system has a small range. The grayscale value of the image pixel obtained by the system after voltage amplification is also in a small range. The dynamic range of the image brightness component is small, which affects the image quality. After obtaining the pixel matrix of the image, the maximum pixel value and the minimum pixel value in the matrix are calculated. Data is used to represent the original pixel value at the current position, NewData is used to represent the grayscale value of the new pixel value after calculation, DataMax is used to represent the maximum pixel value in the image matrix, and DataMin is used to represent the minimum pixel value in the image matrix. According to the number of bits of the image, the maximum grayscale distribution number of the image, Total, is calculated;

[0058]

[0059] Each pixel value in the pixel matrix is ​​calculated by the above formula, and a new pixel value is obtained to replace the original pixel value matrix, thereby completing the preliminary enhancement adjustment of the image brightness.

[0060] Calculate the high and low thresholds of the image after brightness enhancement, redistribute the image pixel matrix values ​​according to the high and low thresholds of the image, complete the image contrast enhancement adjustment, and effectively enhance the image contrast damaged by thermal electron noise interference;

[0061] After the above processing method, the brightness of the high temperature image is adjusted, but the contrast is not optimally adjusted due to the influence of noise, so the contrast needs to be adjusted according to the high and low pixel thresholds of the image;

[0062] Low threshold D min Indicates that the high threshold is represented by D max Indicates that D min The value determines the edge of the area with the lowest pixel value starting from 0 in the adjusted image, D max The value determines the edge of the area with the highest pixel value starting from the maximum grayscale value of the adjusted image. First, the histogram of the image is calculated, and the number of pixels in the histogram is accumulated starting from the pixel value of 0 until the cumulative sum reaches or exceeds S, the total number of pixels in the image, for the first time. low , S low and S high is a percentage value, at this time, the cumulative number of pixels is greater than or equal to the total number of pixels S low The first pixel value is D min ;D max The calculation is to start from the maximum value of the pixel in the image and calculate backward until the number of pixels is greater than or equal to the total number of pixels S high The first pixel value i of max , where total and total_pixel are the total number of pixels in the image.

[0063]

[0064] Reassign image pixel matrix values,

[0065]

[0066] The new pixel value is assigned according to the high and low thresholds. When the pixel value is less than D min All values ​​are assigned to 0. When the pixel value is in D min With D min Redistribution calculation is performed between them. When the pixel value is greater than D min The pixel value is set to the maximum grayscale according to the number of image bits. When all pixels are adjusted, it means that a new image pixel matrix is ​​generated, and the image contrast is enhanced.

[0067] Establish the optimal window model for image filtering, update the window size based on the comparison and judgment with the custom variance threshold, balance the need to preserve image details and remove noise, and minimize the variance of the window pixel value between the processed image and the original image;

[0068] After the above processing method, the brightness and contrast of the image are adjusted. In order to effectively remove the noise of the image, an image filtering optimal window model is constructed according to the idea of ​​adaptive median filtering. For an input image I and a window of size W×W (the window is square), for each pixel (x, y) in the image, the local variance σ is defined2 (x, y), the variance indicates the degree of variation of the pixel value within the window. A larger variance usually means more variation or details in the image area. 2 When (x, y) is large, a larger window is selected. 2 When (x, y) is small, a smaller window is selected to balance the need to retain details and remove noise. Limit and judge by customizing the variance threshold. When it exceeds the set larger variance threshold boundary, it is updated to a large window. When it is less than the set smaller variance threshold boundary, it is updated to a small window. Otherwise, the current window size is maintained.

[0069]

[0070] W is the size of the window, and u(x, y) in the formula represents the mean value of the pixels in the window;

[0071]

[0072] When the optimal filtering window size is determined, for each window of size k×k, it is denoted as W k , Z xy Represents the pixel value at position (x, y) in image g, the minimum value Z in the window min , maximum value Z max and median Z med The calculation method of is as follows. There are two processing steps for calculating the adaptive median filter.

[0073] First, the first judgment, judgment Z med Does Z satisfy max >Z med >Z min If it satisfies, then Z med It is not salt and pepper noise. At this time, keep the window and enter the second judgment to judge Z xy Does Z satisfy max >Z xy >Z min , if the current pixel Z xy Meet Z max >Z xy >Z min , then it means that Z xy If it is not salt and pepper noise, keep the original value; otherwise, use Z med Replace Z xy If Z med Not satisfied with Z max >Z med >Z min , you need to increase the window size until it reaches the preset maximum window size, and repeat the first judgment.

[0074] Zxy =g(x,y)

[0075]

[0076] Z med =median({g(i,j)|(i,j)∈W k})

[0077] After calculation, the noise of the image can be smoothed to the maximum extent without affecting the original details of the image, avoiding excessive blur and distortion.

[0078] Combine multiple image processing results to synthesize new images;

[0079] After the brightness contrast enhancement and filtering are performed on a group of images in the above processing steps, median calculation or mean calculation is performed on each corresponding pixel position of a group of images, and the image pixel matrix is ​​replaced after obtaining the new pixel value, and the quality enhanced result image is generated according to this matrix.

[0080] The first method is to take a set of input images I i (x, y), where i represents the i-th frame image and (x, y) represents the pixel coordinates. For the output image O(x, y), the pixel values ​​are determined by performing median calculation on the pixel values ​​at the same position of multiple images, and then a new image is synthesized. O(x, y) = median{I i (x, y)}

[0081] The median method is used to synthesize multiple images to remove random noise in the image while retaining the details of the image.

[0082] The second method is the mean method. For the output image S(x, y), the corresponding pixel value of the output image is generated by calculating the average value of all pixel values ​​of the corresponding pixel matrix positions of multiple images. i (x, y) is the pixel value at the same position in the i-th input image,

[0083] If the image noise appears in the form of continuous distribution in the image, the noise can be smoothed by synthesizing multiple images into one image through the mean method, thereby improving the overall quality of the image.

[0084] like Figure 1As shown in the figure, the collected images are evaluated using the NIQE image quality evaluation algorithm, which is more in line with the human eye's judgment of image quality than other indicators. This method effectively solves the problems of insufficient or over-adjustment of image brightness contrast and noise amplification when the image collection time is shorter, and avoids the poor image processing effect caused by human subjective judgment parameters. The image quality obtained by this method is better than that of the image collected by the scanning electron microscope.

[0085] The existing processing method is to post-process the obtained high-temperature test images, and the processing order is: obtain high-temperature images for a long time - read - process - re-image, to reduce the influence of some noise or even distortion of the image, while the present method is to process the initial pixel data of the high-temperature test obtained from the acquisition end, and then perform imaging (real-time rapid acquisition and processing, imaging), which not only ensures the real-time nature of the in-situ experiment, but also significantly improves the time efficiency, and the image processing is more accurate, which meets the requirements for rapid imaging under high-temperature tests.

[0086] The above specific implementation modes are used to explain the present invention rather than to limit the present invention. Any modification and change made to the present invention within the spirit of the present invention and the protection scope of the claims shall fall within the protection scope of the present invention.

Claims

1. A method for rapid acquisition and quality enhancement of high-temperature images of scanning electron microscope, It is characterized in that The following steps are involved: Rapidly collect SEM images of high-temperature heated samples to form a matrix of original image pixel values; Redistribute and map the acquired original image pixel value matrix to complete the preliminary enhancement adjustment of the image brightness; Calculate the high and low thresholds of the image after brightness enhancement, redistribute the image pixel matrix values ​​according to the high and low thresholds of the image, and complete the contrast enhancement adjustment of the image; Establish the optimal window model for image filtering, update the window size based on the comparison and judgment with the custom variance threshold, and balance the need to retain image details and remove noise; Combine multiple image processing results to synthesize a new image.

2. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1, Features: The heating temperature of the high-temperature heated sample is greater than or equal to 800° C., and the scanning electron microscope image acquisition speed of the high-temperature heated sample is 170ns / pixel to 320ns / pixel.

3. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1 or 2, Features: In the step of quickly acquiring the scanning electron microscope image of the high-temperature heated sample, an embedded high-temperature image rapid acquisition device is used to perform multiple line-by-line raster scanning acquisitions on the high-temperature heated sample.

4. The method for rapid acquisition and quality enhancement of high temperature images using a scanning electron microscope according to claim 3, Features: The method also includes the following steps: transmitting the collected image pixel value data to the host computer, which starts the sub-thread and adds the collected image data to the sub-thread for processing, and finally displays the image processed by the sub-thread in real time on the main thread display interface of the host computer.

5. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1, Features: In the step of reallocating and mapping the acquired original image pixel value matrix, Calculate each pixel value in the pixel matrix according to the following formula, and get the new pixel value to replace the original pixel value matrix: Among them, NewData represents the new pixel grayscale value after calculation; Data represents the original pixel value at the current position; DataMax represents the maximum pixel value present in the image matrix; DataMin represents the minimum pixel value present in the image matrix; Total represents the maximum grayscale distribution number of the image, which is calculated based on the number of bits of the image.

6. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1, Features: The step of calculating the high and low thresholds of the brightness enhanced image includes the following sub-steps: Define the lower threshold with D min Indicates that D min The value determines the edge of the area with the lowest pixel value starting from 0 in the adjusted image; Define the high threshold with D max Indicates that D max The value determines the edge of the area with the highest pixel value starting from the maximum grayscale value of the adjusted image; Calculate the histogram of the image, starting from the pixel value 0, and accumulate the number of pixels in the histogram until the cumulative sum reaches or exceeds the total number of pixels in the image S for the first time. low , S low and S high is a percentage value, at this time, the cumulative number of pixels is greater than or equal to the total number of pixels S low The first pixel value is D min ; Count backward from the maximum value of the pixel in the image until the number of pixels is greater than or equal to the total number of pixels S high The first pixel value i of max ; Where tothal and total_pixel are the total number of pixels in the image; Redistribute the image pixel matrix values ​​when the pixel value is less than D min All values ​​are assigned to 0. When the pixel value is in D min With D min Redistribution calculation is performed between them. When the pixel value is greater than D min The pixel value is set to the maximum grayscale according to the number of image bits; Until all pixels are adjusted, a new image pixel matrix is ​​generated.

7. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1, Features: The step of establishing the optimal window model for filtering the image, updating the window size based on comparison and judgment with the custom variance threshold, and balancing the need to retain image details and remove noise includes the following sub-steps: For the input image I and a window of size W×W, for each pixel (x, y) in the image, define the local variance σ 2 (x, y), the variance indicates the degree of change of the pixel value within the window; Among them, w is the size of the window, u(x, y) represents the mean value of the pixels in the window, For each window of size k×k, denoted as W k , Z xy Represents the pixel value at position (x, y) in image g, the minimum value Z in the window min , maximum value Z max and median Z med The calculation method is as follows, Z xy =g(x,y); Z med =median({g(i,j)|(i,j)∈W k }); The first judgment, judgment Z med Does Z satisfy max >Z med >Z min If it satisfies, then Z med It is not salt and pepper noise, so keep the window and proceed to the second judgment; The second judgment, judgment Z xy Does Z satisfy max >Z xy >Z min , if the current pixel Z xy Meet Z max >Z xy >Z min , then it means that Z xy It is not salt and pepper noise, so the original value is retained; If the current pixel Z xy Not satisfied with Z max >Z xy >Z min , then use Z med Replace Z xy The value of If Z med Not satisfied with Z max >Z med >Z min , you need to increase the window size until it reaches the preset maximum window size, and repeat the first judgment.

8. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1, Features: In the step of combining the processing results of multiple images to synthesize a new image, for a set of input images I i (x, y), where i represents the i-th frame image, (x, y) represents the pixel coordinates, and for the output image O(x, y), the pixel values ​​are determined by median calculation of the pixel values ​​at the same position of multiple images, and then a new image is synthesized, o(x, y) = median{I i (x, y)}.

9. The method for rapid acquisition and quality enhancement of high temperature images of a scanning electron microscope according to claim 1, Features: In the step of synthesizing a new image by combining the processing results of multiple images, for the output image S(x, y), the corresponding pixel value of the output image is generated by calculating the average value of all pixel values ​​of the corresponding pixel matrix positions of the multiple images, I i (x, y) is the pixel value at the same position in the i-th input image,

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