Lightning squeak feature parameter extraction method based on image processing and connected domain analysis

Abstract

The invention discloses a lightning squeak characteristic parameter extraction method based on image processing and connected domain analysis. The method comprises the following steps: sequentially carrying out gray processing and binarization processing on an obtained lightning squeak time-frequency signal; on the basis of a binarization processing result, performing closed operation, and connecting fractured parts of the dispersion spectrum; performing connected domain analysis based on the image after fracture recovery of the dispersion spectrum, and determining a connected region; and extracting pixel point information of each lightning squeak wave dispersion spectrum based on the determined connected region, obtaining a time-frequency information set of each lightning squeak wave dispersion spectrum through conversion from the pixel point information to time-frequency information, and then fitting to obtain lightning squeak characteristic parameters. According to the invention, by combining the image processing and connected domain analysis technology, the automatic extraction of the lightning squeak signal is realized, and the problems of weak anti-interference capability, low recognition rate and limited recognition types of the traditional automatic recognition method for more complex squeak recognition are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of lightning squeak signal processing, and specifically to a method for extracting lightning squeak characteristic parameters based on image processing technology and connected domain analysis technology. Background Art

[0002] The channel length of ground lightning in lightning activities is generally several kilometers, the peak current can reach tens of thousands of amperes, and the entire discharge time is generally no more than one second. The release of such a strong lightning current in a very short time makes lightning extremely destructive. Direct lightning may cause forest fires and building destruction, and will also hinder the normal operation of industries such as electricity, communications, chemical industry and meteorology. The high temperature, shock waves and strong electromagnetic radiation accompanying lightning may also bring huge personal safety hazards and property losses. Lightning electromagnetic pulse (LEMP) can generate induced overvoltage in electronic and electrical equipment or high-voltage transmission lines, indirectly causing damage to equipment, and accidents are also common.

[0003] With the rapid development of the country's modernization process, the scope of human activities has been continuously expanded, and the awareness of lightning protection has become stronger and stronger. Therefore, it is of great significance to study the physical mechanisms of lightning in thunderstorm cloud formation conditions, lightning development process, lightning electromagnetic wave propagation characteristics, and lightning protection methods. Studying the propagation characteristics of the electromagnetic field generated by lightning activity is a necessary means in lightning detection. The frequency band of the lightning electromagnetic field generated in a lightning process covers extremely low frequency (ELF) to ultra-high frequency (UHF), and the propagation characteristics of electromagnetic waves in different frequency bands are different, which are suitable for various research scopes. Signal receiving antennas of different frequency bands can be developed to study the various development processes and discharge parameters of lightning. In the main discharge process, that is, the return stroke process, the high-frequency electromagnetic field (HF) generated will be affected by factors such as soil conductivity and rapidly attenuated, but the low-frequency (VLF) and very low-frequency (LF) electromagnetic waves with relatively concentrated radiation energy can propagate along the surface for thousands of kilometers or even farther.

[0004] An earlier development is to use traditional image processing methods and template matching theory to identify lightning whistle waves. The Stanford VLF Group denoised and gridded the time-frequency diagram of the DEMETER satellite, calculated the average amplitude value of each grid to obtain feature representation, and then made a lightning whistle wave template. The image template and the time-frequency diagram to be detected were convolved to obtain a similarity measure, and a similarity measure threshold was set as the basis for judging whether it is a lightning whistle wave. Similarly, Fiser made two lightning whistle wave templates for daytime and night based on DEMETER satellite data, and proposed a 0+ whistle recognition algorithm based on a two-dimensional cross-correlation function. Oike believes that the dispersion of lightning whistle waves should not be a constant, so he made whistle templates with different dispersions based on Fiser, and used the original time-frequency diagram observed by the Akebono satellite. Figure 2 After the image is binarized into a grayscale image, template matching is performed. Ali Ahmad believes that the above method is mixed with a lot of noise. He uses Gaussian smoothing algorithm and Laplace filtering to remove the noise in the time-frequency graph, and uses Bresenham algorithm to detect the lightning whistle wave curve after binarization. Dharma uses the connectivity of lightning whistle waves and uses the connected domain analysis method to identify the trajectory of lightning whistle waves. Dharma uses image processing methods such as binarization, median filtering, and open operations to deal with noise and interference in the time-frequency graph. Finally, the seed filling method is used to find the connected area of ​​lightning whistle waves from the time-frequency graph and mark them.

[0005] The traditional image processing methods used in the above studies have limited ability to denoise time-frequency diagrams, and the recognition process is very sensitive to time-frequency noise, resulting in a low recognition rate. At the same time, the template matching theory used in the above studies can only recognize a single spectrum curve with little difference in time width, and the recognition types are very limited. Therefore, the traditional automatic recognition method has many disadvantages for more complex squeak recognition, such as weak anti-interference ability, low recognition rate and limited recognition types. Summary of the invention

[0006] In order to solve the problems of weak anti-interference ability, low recognition rate and limited recognition types of traditional automatic recognition methods for more complex squeak recognition, the present invention provides a lightning squeak feature parameter extraction method based on image processing and connected domain analysis. By combining image processing and connected domain analysis technology, automatic extraction of lightning squeak signals is achieved with strong anti-interference ability.

[0007] According to one aspect of the present invention, a method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis is provided, comprising:

[0008] The obtained lightning squeaking time-frequency signal is processed in grayscale and binarized in turn;

[0009] Based on the binarization results, a closing operation is performed to connect the broken parts of the dispersion spectrum;

[0010] Based on the image after the dispersion spectrum is broken and restored, the connected domain analysis is performed to determine the connected area;

[0011] Based on the determined connected area, the pixel information of each lightning squeak wave dispersion spectrum is extracted, and the time-frequency information set of each lightning squeak wave dispersion spectrum is obtained by converting the pixel information into time-frequency information, and then the lightning squeak characteristic parameters are fitted.

[0012] As a further technical solution, when performing connected domain analysis, traverse the image, and if the pixel value is 1, perform the following operations:

[0013] a takes the current pixel as the seed and assigns a new label, then adds the positions of the pixels of interest in all its areas to the stack;

[0014] b Pop the pixel at the top of the stack, assign the same label, and add the positions of the pixels of interest in all its areas to the stack;

[0015] c Repeat step b until the stack is empty, then a connected region is found and marked with the same label.

[0016] As a further technical solution, after extracting the pixel information of each lightning squeak sound wave dispersion spectrum, the pixel information is converted into time-frequency information according to the following formula:

[0017]

[0018] Among them, Lw represents the width of the pixel in the time-frequency graph, Lh represents the height of the pixel in the time-frequency graph, Lt represents the time width in the time-frequency graph, Lf represents the frequency width in the time-frequency graph, (r, c) represents the position of a pixel in the time-frequency graph, and (t, f) represents the time-frequency information corresponding to the pixel.

[0019] As a further technical solution, after obtaining the time-frequency information set of each lightning squeak wave dispersion spectrum, the least squares fitting is performed on the time-frequency set according to the following formula to obtain the lightning squeak characteristic parameters:

[0020]

[0021] Among them, t0 represents the time when lightning occurs, D represents the dispersion coefficient of lightning squeak sound waves, and k represents the frequency-related order.

[0022] As a further technical solution, when performing a closing operation, it includes: performing a closing operation on the binary image and a structure operator, wherein the structure operator adopts a 20×5 rectangular structure operator.

[0023] According to one aspect of the present invention, there is provided a lightning squeak feature parameter extraction device based on image processing and connected domain analysis, comprising:

[0024] An image processing module is used to sequentially perform grayscale processing and binarization processing on the acquired lightning squeaking time-frequency signal, and based on the binarization processing result, perform a closing operation to connect the broken parts of the dispersion spectrum;

[0025] A connected domain analysis module is used to perform connected domain analysis based on the image after the dispersion spectrum is broken and restored to determine the connected area;

[0026] The characteristic parameter extraction module is used to extract the pixel point information of each lightning squeak sound wave dispersion spectrum based on the determined connected area, and obtain the time-frequency information set of each lightning squeak sound wave dispersion spectrum by converting the pixel point information into time-frequency information, and then fit the lightning squeak characteristic parameters.

[0027] According to one aspect of the present invention, there is provided a device for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis, comprising a memory and a processor, wherein the memory stores program instructions to be executed by the processor, and the processor calls the program instructions to execute the steps of the method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis.

[0028] According to one aspect of the present specification, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, wherein the computer instructions enable the computer to execute the steps of the method for extracting lightning squeak characteristic parameters based on image processing and connected domain analysis.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention provides a method for extracting characteristic parameters of lightning squeak based on image processing technology and connected domain analysis technology. Through the interaction of grayscale processing and binarization processing, closed operation connecting the broken parts of the dispersion spectrum, connected domain analysis and LW physical parameter extraction, the automatic extraction of characteristic parameters of lightning squeak under the combination of image processing technology and connected domain analysis technology is realized. The present invention can extract signals with poor signal quality or low signal-to-noise ratio by first recovering the dispersion spectrum and then analyzing the connected domain, ensuring that the lightning squeak signal is automatically extracted under the premise of improving the anti-interference effect, recognition rate and recognition type. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief introduction is given below to the drawings used in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1 A schematic flow chart of a method for extracting characteristic parameters of lightning squeak sound based on image processing and connected domain analysis provided in an embodiment of the present invention.

[0033] Figure 2 A schematic diagram of a binary image provided by an embodiment of the present invention.

[0034] Figure 3 A schematic diagram of the closing operation processing result provided by an embodiment of the present invention.

[0035] Figure 4 (a)-(b) are schematic diagrams of the correspondence between pixel points and time-frequency points provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. In addition, the technical features in the various embodiments or single embodiments provided by the present invention are arbitrarily combined with each other to form a new technical solution. This combination is not restricted by the sequence of steps and / or the structural composition mode, but must be based on the ability of ordinary technicians in this field to achieve. When the combination of technical solutions is contradictory or cannot be achieved, it should be considered that this combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0037] The method for extracting lightning squeak characteristic parameters based on image processing and connected domain analysis in this embodiment first performs image processing on the acquired lightning squeak time-frequency signal, including grayscale processing and binarization processing, and performs a closed operation to connect the broken parts of the dispersion spectrum after the binarization processing, so as to be more conducive to the connected domain analysis; then a connected domain analysis is performed on the processed image to determine the connected area; finally, based on the determined connected area, the pixel information of each lightning squeak wave dispersion spectrum trajectory is extracted, and the time-frequency information set of each lightning squeak wave dispersion spectrum is obtained by converting the pixel information into time-frequency information, and then the lightning squeak characteristic parameters are fitted.

[0038] Please refer to Figure 1 , the method of this embodiment specifically includes the following steps:

[0039] S1 Grayscale processing and binarization processing:

[0040] The segmentation result of the lightning squeak time-frequency signal is a three-channel RGB image. First, convert the three-channel RGB image into a single-channel grayscale image, and then use the threshold segmentation algorithm in traditional image processing methods to perform binarization processing on the grayscale image. The steps of the threshold segmentation algorithm are as follows:

[0041] Assume that the coordinates of the current pixel point are (x, y), the neighborhood centered on this point is r*r, and g(x, y) represents the grayscale value at (x, y). The first step of the threshold segmentation algorithm is to calculate the grayscale mean m(x, y) and standard variance s(x, y) within the neighborhood r*r:

[0042]

[0043] Then calculate the threshold T(x, y) of the pixel point (x, y):

[0044]

[0045] where R is the dynamic range of the standard variance, k is a correction coefficient, and the value range is 0 < k < 1. The value of k has little influence on the algorithm;

[0046] Then the thresholded image f(x, y) is defined as:

[0047]

[0048] S2 Closing operation to connect the broken parts of the dispersion spectrum:

[0049] In the lightning squeak wave dispersion spectrum, some places with weak energy will break, which will affect the connectivity of the dispersion spectrum and bring difficulties to the subsequent connected component analysis. Therefore, this embodiment uses the closing operation in traditional image processing methods to reconnect the broken areas. The closing operation is defined as follows:

[0050]

[0051] where A is Figure 2 the binary image shown, B is the structuring element, and this embodiment uses a 20×5 rectangular structuring element, represents the dilation operation, Represents the erosion operation. The dilation operation is the process of increasing the pixels at the boundary of the target in the digital image, and the erosion operation is the process of reducing the pixels at the boundary of the target. The number of pixels increased or reduced depends on the form and size of the structural element used. The closing operation fills the broken area inside the LW dispersion spectrum trajectory by first dilating and then eroding, thereby ensuring good connectivity of the LW trajectory. The closing operation result is as follows: Figure 3 shown.

[0052] S3 connectivity domain analysis:

[0053] Connected domain analysis is a very common image processing operation. Connected domain analysis is generally used for binary images. It finds and marks adjacent pixels with the same pixel value. The LW trajectory after the closed operation has obvious connectivity. The seed filling method can be used to analyze and extract each connected region. The seed filling method starts from a seed and searches around the domain. If equal pixel values ​​are found, they are marked with the same label, and then continue to search in the domain until there are no identical pixel values ​​around. A connected region is found, and then other seeds are used to continue searching the next connected region. The seed here is a pixel of interest.

[0054] The specific process is as follows:

[0055] Iterate over the image, and if the pixel value is 1, do the following:

[0056] a takes the current pixel as the seed and assigns a new label, then adds the positions of all pixels of interest (value greater than 1) in its field to the stack;

[0057] b Pop the pixel at the top of the stack, assign it the same label, and add the positions of all pixels of interest (value greater than 1) in its area to the stack;

[0058] c. Repeat step b until the stack is empty;

[0059] At this time, a connected area is found and marked with the same label.

[0060] S4 LW physical parameters extraction:

[0061] Eckersley's law reveals the simple relationship between the frequency f of the lightning squeak wave and the arrival time t, as follows:

[0062]

[0063] Wherein t is the arrival time of the lightning squeak wave with a frequency of f, that is, the satellite reception time, D is the dispersion coefficient of the lightning squeak wave, referred to as dispersion, t0 is the time when lightning occurs, and the dispersion D and the lightning occurrence time t0 are the physical parameters of the lightning squeak wave that need to be extracted in this embodiment, and k represents the frequency-related order.

[0064] After the connected domain analysis in the previous step, this embodiment extracts the pixel information of each lightning squeak wave dispersion spectrum trajectory, such as Figure 4 (a) shows the pixel information of the time-frequency graph. The point (r, c) is used to represent the position of a pixel in the time-frequency graph. The width of the pixel in the time-frequency graph is set to Lw, and the height is set to Lh. Figure 4 (b) is the time-frequency information of the time-frequency diagram. The time width in the time-frequency diagram is Lt, the frequency width is Lf, and (t, f) is used to represent the time-frequency information corresponding to the pixel point (r, c). The relationship between the two is as follows:

[0065]

[0066] The pixel information of the LW dispersion spectrum is converted into time-frequency information by the above method, and the time-frequency information set of each LW dispersion spectrum is obtained {(t i ,f i )|i=1,2,···,n}, where n is the number of pixels of a LW dispersion spectrum. The relationship between the lightning squeak wave frequency f and the arrival time t is fitted by least squares on this time-frequency information set to obtain the LW physical parameters D, k and t0.

[0067] The above embodiment realizes the extraction of lightning squeak characteristic parameters by combining image processing technology and connected domain analysis technology through S1 grayscale processing and binarization processing, S2 closing operation to connect the broken parts of the dispersion spectrum, S3 connected domain analysis and S4 LW physical parameter extraction, thereby ensuring the automatic extraction of lightning squeak signals under the premise of improving the anti-interference effect, recognition rate and recognition type and other defects of the existing technologies.

[0068] The implementation basis of each embodiment of the present invention is to implement programmed processing through a device with a processor function. Therefore, in engineering practice, the technical solutions and functions of each embodiment of the present invention are encapsulated into various modules. Based on this reality, on the basis of the above embodiments, an embodiment of the present invention provides a lightning squeak feature parameter extraction device based on image processing and connected domain analysis, and the device is used to execute the lightning squeak feature parameter extraction method based on image processing and connected domain analysis in the above method embodiment.

[0069] The device includes: an image processing module, which is used to perform grayscale processing and binarization processing on the acquired lightning squeak time-frequency signal in sequence, and perform a closing operation based on the binarization processing result to connect the broken parts of the dispersion spectrum; a connected domain analysis module, which is used to perform a connected domain analysis based on the image after the dispersion spectrum is restored, and determine the connected area; a characteristic parameter extraction module, which is used to extract the pixel point information of the dispersion spectrum of each lightning squeak wave based on the determined connected area, and obtain the time-frequency information set of the dispersion spectrum of each lightning squeak wave by converting the pixel point information into the time-frequency information, and then fit the lightning squeak characteristic parameters.

[0070] The lightning squeak feature parameter extraction device based on image processing and connected domain analysis provided in the embodiment of the present invention aims to solve the problems that traditional automatic recognition methods have many shortcomings for more complex squeak recognition, such as weak anti-interference ability, low recognition rate and limited recognition types. By adopting the above-mentioned several modules and combining image processing and connected domain analysis technology, the automatic extraction of lightning squeak signals is realized with strong anti-interference ability.

[0071] It should be noted that the device embodiments provided by the present invention are used to implement the methods in the above method embodiments as well as the methods in other method embodiments provided by the present invention. The only difference is that the corresponding functional modules are set, and the principle is basically the same as the principle of the above device embodiments provided by the present invention. As long as the technical personnel in the field refer to the specific technical solutions in other method embodiments on the basis of the above device embodiments, obtain the corresponding technical means and the technical solutions composed of these technical means by combining the technical features, and on the premise of ensuring the practicality of the technical solutions, they can improve the devices in the above device embodiments to obtain the corresponding device class embodiments, which are used to implement the methods in other method class embodiments. For example:

[0072] Based on the content of the above device embodiment, as a preferred embodiment, the lightning squeak feature parameter extraction device based on image processing and connected domain analysis provided in the embodiment of the present invention, the connected domain analysis module is also used to execute the following instructions:

[0073] Iterate over the image, and if the pixel value is 1, do the following:

[0074] a takes the current pixel as the seed and assigns a new label, then adds the positions of the pixels of interest in all its areas to the stack;

[0075] b Pop the pixel at the top of the stack, assign the same label, and add the positions of the pixels of interest in all its areas to the stack;

[0076] c Repeat step b until the stack is empty, then a connected region is found and marked with the same label.

[0077] Based on the contents of the above device embodiments, as a preferred embodiment, the lightning squeak feature parameter extraction device based on image processing and connected domain analysis provided in the embodiments of the present invention, the feature parameter extraction module is also used to convert the pixel point information into time-frequency information according to the following formula after extracting the pixel point information of each lightning squeak wave dispersion spectrum:

[0078]

[0079] Among them, Lw represents the width of the pixel in the time-frequency graph, Lh represents the height of the pixel in the time-frequency graph, Lt represents the time width in the time-frequency graph, Lf represents the frequency width in the time-frequency graph, (r, c) represents the position of a pixel in the time-frequency graph, and (t, f) represents the time-frequency information corresponding to the pixel.

[0080] Based on the contents of the above device embodiments, as a preferred embodiment, the lightning squeak characteristic parameter extraction device based on image processing and connected domain analysis provided in the embodiments of the present invention, the characteristic parameter extraction module is also used to obtain the time-frequency information set of each lightning squeak wave dispersion spectrum, and then perform least square fitting on the time-frequency set according to the following formula to obtain the lightning squeak characteristic parameters:

[0081]

[0082] Among them, t0 represents the time when lightning occurs, D represents the dispersion coefficient of lightning squeak sound waves, and k represents the frequency-related order.

[0083] Based on the same inventive concept as the above-mentioned embodiment, an embodiment of the present invention also provides a lightning squeak feature parameter extraction device based on image processing and connected domain analysis, including a memory and a processor, the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of the lightning squeak feature parameter extraction method based on image processing and connected domain analysis.

[0084] Based on the same inventive concept as the above-mentioned embodiment, the embodiment of the present invention also provides a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions enable the computer to execute the steps of the lightning squeak feature parameter extraction method based on image processing and connected domain analysis.

[0085] In addition, when the logic instructions in the above-mentioned at least one memory are implemented in the form of a software functional unit and sold or used as an independent product, they are stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or partly in other words, the part that contributes to the prior art or part of the technical solution is embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions for enabling a computer device (a personal computer, a server, or a network device) to perform all or part of the steps of the method described in each method embodiment of the present invention. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a disk or an optical disk, and various media for storing program codes.

[0086] It should be noted that in the present specification, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis, characterized in that: include: The obtained lightning squeaking time-frequency signal is processed in grayscale and binarized in turn; Based on the binarization results, a closing operation is performed to connect the broken parts of the dispersion spectrum; Based on the image after the dispersion spectrum is broken and restored, the connected domain analysis is performed to determine the connected area; Based on the determined connected area, the pixel information of each lightning squeak wave dispersion spectrum is extracted, and the time-frequency information set of each lightning squeak wave dispersion spectrum is obtained by converting the pixel information into time-frequency information, and then the lightning squeak characteristic parameters are fitted.

2. The method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis according to claim 1 is characterized in that: When performing connected domain analysis, traverse the image and if the pixel value is 1, perform the following operations: a takes the current pixel as the seed and assigns a new label, then adds the positions of the pixels of interest in all its areas to the stack; b Pop the pixel at the top of the stack, assign the same label, and add the positions of the pixels of interest in all its areas to the stack; c Repeat step b until the stack is empty, then a connected region is found and marked with the same label.

3. The method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis according to claim 1 is characterized in that: After extracting the pixel information of each lightning squeak wave dispersion spectrum, the pixel information is converted into time-frequency information according to the following formula: Among them, Lw represents the width of the pixel in the time-frequency graph, Lh represents the height of the pixel in the time-frequency graph, Lt represents the time width in the time-frequency graph, Lf represents the frequency width in the time-frequency graph, (r, c) represents the position of a pixel in the time-frequency graph, and (t, f) represents the time-frequency information corresponding to the pixel.

4. The method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis according to claim 3 is characterized in that: After obtaining the time-frequency information set of each lightning squeak wave dispersion spectrum, the least squares fitting is performed on the time-frequency set according to the following formula to obtain the lightning squeak characteristic parameters: Among them, t0 represents the time when lightning occurs, D represents the dispersion coefficient of lightning squeak sound waves, and k represents the frequency-related order.

5. The method for extracting characteristic parameters of lightning squeak based on image processing and connected domain analysis according to claim 1 is characterized in that: When performing the closing operation, it includes: performing a closing operation on the binary image and the structure operator, wherein the structure operator adopts a 20×5 rectangular structure operator.

6. A lightning squeak characteristic parameter extraction device based on image processing and connected domain analysis, characterized in that: include: An image processing module is used to sequentially perform grayscale processing and binarization processing on the acquired lightning squeaking time-frequency signal, and based on the binarization processing result, perform a closing operation to connect the broken parts of the dispersion spectrum; A connected domain analysis module is used to perform connected domain analysis based on the image after the dispersion spectrum is broken and restored to determine the connected area; The characteristic parameter extraction module is used to extract the pixel point information of each lightning squeak sound wave dispersion spectrum based on the determined connected area, and obtain the time-frequency information set of each lightning squeak sound wave dispersion spectrum by converting the pixel point information into time-frequency information, and then fit the lightning squeak characteristic parameters.

7. A lightning squeak characteristic parameter extraction device based on image processing and connected domain analysis, characterized in that: It includes a memory and a processor, the memory stores program instructions executed by the processor, and the processor calls the program instructions to execute the steps of the lightning squeak feature parameter extraction method based on image processing and connected domain analysis as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium stores computer instructions, which enable the computer to execute the steps of the lightning squeak feature parameter extraction method based on image processing and connected domain analysis as described in any one of claims 1 to 5.

Images