Infrared Imaging Simulation Method and System Based on Data Analysis

Abstract

The present invention relates to the field of infrared thermal imaging technology, and particularly relates to an infrared imaging simulation method and system based on data analysis. First, according to the difference in the infrared radiation values of pixel points in the initial infrared imaging of a bullet, each suspected bullet pixel point is screened out from all pixel points; according to the infrared radiation values of pixel points in the real bullet area, each pixel point to be corrected is screened out; according to the infrared radiation values in the local area of the pixel point to be corrected, the corrected infrared radiation value of the pixel point to be corrected is obtained; according to the corrected infrared radiation values of all pixel points to be corrected, the initial infrared imaging of the bullet is corrected to obtain the corrected infrared imaging of the bullet; according to the corrected infrared imaging of the bullet, an infrared image simulation model is generated. By deeply analyzing the influence of particulate matter on the infrared radiation value, the present invention constructs a corrected infrared imaging of the bullet to more accurately reflect the actual infrared radiation characteristics of the bullet, thereby improving the accuracy of the generated infrared image simulation model.

Description

Technical Field

[0001] The present invention relates to the field of infrared thermal imaging technology, and in particular to an infrared imaging simulation method and system based on data analysis. Background Art

[0002] Infrared imaging technology is a technology that converts the infrared radiation of the environment and the target into a visible image that can be identified, thereby revealing key information about the target and its background. In infrared imaging simulation, the first step is to accurately establish the relationship between the surface temperature of the object and the infrared radiation value it releases. Then, through meticulous image rendering and parameter fine-tuning, a realistic infrared image simulation model can be generated, which can provide important technical support and decision-making basis.

[0003] The existing technology directly generates a bullet infrared image simulation model based on the collected initial infrared image of the bullet. It does not fully consider that due to the uncontrollability of the bullet's flight environment, there are some tiny particles attached to the bullet surface. The particles will affect the reception of the real infrared radiation value released during the bullet's flight, resulting in inaccurate collection of the bullet's initial infrared image, affecting the accuracy of the infrared image simulation model. Summary of the invention

[0004] In order to solve the technical problem of inaccurate infrared imaging constructed by the prior art, the purpose of the present invention is to provide an infrared imaging simulation method and system based on data analysis, and the technical solution adopted is as follows:

[0005] An infrared imaging simulation method based on data analysis, the method comprising:

[0006] Acquire the initial infrared imaging of the bullet during its flight;

[0007] According to the difference of the infrared radiation values ​​of the pixels in the initial infrared imaging of the bullet, each suspected bullet pixel is screened out from all the pixels; according to all the suspected bullet pixels in the initial infrared imaging of the bullet, each suspected bullet area is determined; according to the deviation of the suspected bullet area from the standard, the real bullet area is screened out;

[0008] Filter out the pixels to be corrected according to the infrared radiation values ​​of the pixels in the real bullet area; obtain the corrected infrared radiation values ​​of the pixels to be corrected according to the infrared radiation values ​​in the local area of ​​the pixels to be corrected; correct the initial infrared imaging of the bullet according to the corrected infrared radiation values ​​of all the pixels to be corrected to obtain the corrected infrared imaging of the bullet; generate an infrared image simulation model according to the corrected infrared imaging of the bullet.

[0009] Furthermore, the method for obtaining the suspected bullet pixel point includes:

[0010] In the initial infrared imaging of the bullet, according to the difference between the infrared radiation value of the pixel and the overall infrared radiation value of the initial infrared imaging of the bullet, obtain the bullet possibility of the pixel;

[0011] Mark each pixel point with a bullet possibility greater than the preset infrared threshold as each suspected bullet pixel point.

[0012] Further, the method for obtaining the bullet possibility includes:

[0013] Calculate the mean value of the infrared radiation values corresponding to all pixel points in the initial infrared imaging of the bullet to obtain the overall infrared radiation value of the initial infrared imaging of the bullet; calculate the difference between the infrared radiation value of the pixel and the overall infrared radiation value and perform normalization processing to obtain the bullet possibility of the pixel.

[0014] Further, the method for obtaining the real bullet area includes:

[0015] Take the suspected bullet area and the preset standard bullet as the areas to be measured respectively; calculate the cumulative value of the curvature values corresponding to all feature points on the edge of the area to be measured as the shape curvature value of the area to be measured; calculate the absolute value of the difference between the shape curvature values of the suspected bullet area and the preset standard bullet and perform negative correlation mapping to obtain the real possibility of the suspected bullet area;

[0016] Take the suspected bullet area corresponding to the maximum real possibility as the real bullet area.

[0017] Further, the method for obtaining the pixel points to be corrected includes:

[0018] According to the direction feature of the real bullet area, obtain the first influence degree of the particulate matter on the real bullet area;

[0019] According to the difference between the infrared radiation value of the pixel and its local infrared radiation value, obtain the second influence degree of the particulate matter on the pixel;

[0020] Positively fuse the first influence degree of the particulate matter and the second influence degree of the particulate matter corresponding to the pixel to obtain the comprehensive influence degree of the particulate matter on the pixel;

[0021] According to the comprehensive influence degree of the particulate matter, screen out each pixel point to be corrected from all pixel points of the real bullet area.

[0022] Further, the method for obtaining the first influence degree of the particulate matter includes:

[0023] Using the principal component analysis method, the main direction of the real bullet area is taken as the flight direction of the real bullet area; the direction perpendicular to the ground is taken as the reference direction; the included angle value between the flight direction and the reference direction is negatively correlated and mapped to obtain the first influence degree of the particulate matter in the real bullet area.

[0024] Further, the method for obtaining the second influence degree of the particulate matter includes:

[0025] On the flight direction, the average value of the corresponding infrared radiation values of the previous pixel point and the next pixel point of the pixel point is used as the local infrared radiation value of the pixel point; the absolute value of the difference between the infrared radiation value of the pixel point and the local infrared radiation value is calculated to obtain the second influence degree of the particulate matter of the pixel point.

[0026] Further, the method for obtaining the comprehensive influence degree of the particulate matter includes:

[0027] Calculate the product of the first influence degree of the particulate matter and the second influence degree of the particulate matter corresponding to the pixel point and perform normalization processing to obtain the comprehensive influence degree of the particulate matter of the pixel point.

[0028] Further, the method for obtaining the corrected infrared radiation value includes:

[0029] In the preset local area of the pixel point to be corrected, each pixel point except the pixel point to be corrected is used as a reference pixel point; the average value of the infrared radiation values of all reference pixel points is calculated as the corrected infrared radiation value of the pixel point to be corrected.

[0030] The present invention provides an infrared imaging simulation system based on data analysis, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the infrared imaging simulation method based on data analysis are implemented.

[0031] The present invention has the following beneficial effects:

[0032] Considering that the surface temperature of the bullet is usually higher than the surrounding environment, the infrared radiation value of the pixel corresponding to the bullet will be relatively high. Suspected bullet pixels are screened out from all pixels; the deviation of the suspected bullet area from the standard bullet is analyzed for further screening, and the suspected bullet area that conforms to the bullet shape characteristics is retained as the real bullet area. Considering the influence of particulate matter on the bullet, according to the infrared radiation value of the pixels in the real bullet area, the pixels to be corrected caused by the influence of tiny particles are screened out. For the screened pixels to be corrected, the corrected infrared radiation value needs to be obtained according to the infrared radiation value in the local area of these pixels to make it closer to the real value. After obtaining the corrected infrared radiation values of all the pixels to be corrected, the initial infrared imaging of the bullet can be corrected as a whole, so that the corrected infrared imaging of the bullet can more accurately reflect the actual infrared radiation characteristics of the bullet, thereby improving the accuracy of the generated infrared image simulation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0034] Figure 1 It is a flowchart of a method for simulating infrared imaging based on data analysis provided by an embodiment of the present invention;

[0035] Figure 2 It is a flowchart of a method for obtaining suspected bullet pixels provided by an embodiment of the present invention;

[0036] Figure 3 It is a flowchart of a method for obtaining pixels to be corrected provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following combines the drawings and preferred embodiments to detail the specific implementation manners, structures, features and effects of a method and system for simulating infrared imaging based on data analysis proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0039] The following specifically describes the specific solutions of an infrared imaging simulation method and system provided by the present invention in conjunction with the accompanying drawings.

[0040] An embodiment of the present invention provides an infrared imaging simulation method and system based on data analysis. Please refer to Figure 1 , which shows a flowchart of an infrared imaging simulation method provided by an embodiment of the present invention. The method includes the following steps:

[0041] Step S1: Obtain the initial infrared imaging of the bullet during the flight of the bullet.

[0042] First, install the infrared thermal imager at a suitable position so that it can capture the initial infrared imaging of the bullet flight. Ensure that the lens of the infrared thermal imager maintains a certain angle and distance from the bullet flight trajectory to obtain the best infrared imaging effect. Fire the bullet and simultaneously start the infrared thermal imager to capture. The infrared thermal imager collects the bullet during the bullet flight at a preset frequency, and obtains the original collected images corresponding to the bullet at each sampling moment. Since there is noise in the collected original collected images, and the noise will affect the subsequent edge detection, the original collected images are denoised to eliminate the influence caused by noise and partial external interference, and enhance the accuracy of subsequent analysis, so as to obtain the initial infrared imaging of the bullet. In the embodiment of the present invention, median filtering is used to denoise the image, and the implementer can set the denoising method according to the actual situation. In an embodiment of the present invention, sampling is performed at a preset frequency, and each sampling is used as a sampling moment, and the preset frequency is 5 times / second.

[0043] It should be noted that, for the convenience of calculation, all the index data involved in the operation in the embodiment of the present invention have undergone data preprocessing, thereby eliminating the influence of dimensions. The specific means of eliminating the dimension influence are well-known technical means to those skilled in the art and will not be limited here. It should be noted that the present invention performs image acquisition on the target bullet during the upward flight process, and the initial infrared imaging of the bullet only includes one bullet, that is, the target bullet.

[0044] Considering that in the case of the high-speed flight of the bullet, static electricity may be generated on its surface due to friction with the air, thereby attracting more tiny particles. These particles will interfere with the capture of the true infrared radiation value of the bullet by the infrared imaging device, resulting in a deviation between the initial infrared imaging of the bullet and the actual infrared radiation characteristics of the bullet. In order to correct this inaccurate infrared radiation value, it is first necessary to accurately identify the bullet area from the initial infrared imaging of the bullet.

[0045] Step S2: According to the difference in the infrared radiation values of the pixel points in the initial infrared image of the bullet, screen out each suspected bullet pixel point from all the pixel points; determine each suspected bullet area based on all the suspected bullet pixel points in the initial infrared image of the bullet; and screen out the real bullet area according to the deviation standard of the suspected bullet area.

[0046] Considering that the surface temperature of the bullet is usually higher than the surrounding environment, the infrared radiation value of the pixel points corresponding to the bullet will be relatively high. Screen out the suspected bullet pixel points from all the pixel points; analyze the deviation standard of the suspected bullet area from the standard bullet situation, and conduct further screening to retain the suspected bullet area that conforms to the bullet shape characteristics as the real bullet area.

[0047] Considering that during the flight of the bullet, due to air friction and other situations, the bullet will have a greater temperature performance compared to the environment, and this temperature difference is reflected in the initial infrared image of the bullet. Specifically, it is manifested as the pixel points corresponding to the bullet having a higher infrared radiation value. Each pixel point in the infrared image has a corresponding infrared radiation value. By comparing the difference in the infrared radiation values of the pixel points and the initial infrared image of the bullet, screen out the pixel points reflecting the bullet from all the pixel points in the initial infrared image of the bullet. Please refer to Figure 2 , which shows a flowchart of a method for obtaining suspected bullet pixel points in an embodiment of the present invention. Preferably, in an embodiment of the present invention, the method for obtaining suspected bullet pixel points includes:

[0048] Step S201: In the initial infrared image of the bullet, obtain the bullet possibility of the pixel point according to the difference between the infrared radiation value of the pixel point and the overall infrared radiation value of the initial infrared image of the bullet.

[0049] By constructing the bullet possibility of the pixel point, initially reflect the possibility of the pixel point corresponding to the bullet.

[0050] Preferably, in an embodiment of the present invention, the method for obtaining the bullet possibility includes:

[0051] Calculate the mean value of the infrared radiation values corresponding to all the pixel points in the initial infrared image of the bullet to obtain the overall infrared radiation value of the initial infrared image of the bullet; calculate the difference between the infrared radiation value of the pixel point and the overall infrared radiation value and perform normalization processing to obtain the bullet possibility of the pixel point. It should be noted that the method of normalization is as follows: Use the norm normalization function for normalization to limit the numerical range between 0 and 1. Among them, normalization is a well-known technical means in the art, and the choice of the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited herein.

[0052] For the above steps, first, calculate the mean of the infrared radiation values of all pixel points in the initial infrared image of the bullet to obtain the overall infrared radiation value of the initial infrared image of the bullet. The overall infrared radiation value reflects the temperature of the overall environment. Next, for each pixel point, calculate the difference between its infrared radiation value and the overall infrared radiation value. This difference reflects the temperature difference of this pixel point relative to the overall environment. To make this difference comparable, perform normalization processing on it to obtain the bullet likelihood of the pixel point. The higher the bullet likelihood of a pixel point, the more likely it is to be the corresponding pixel point of the bullet.

[0053] Step S202: Mark each pixel point with a bullet likelihood greater than the preset infrared threshold as each suspected bullet pixel point.

[0054] For the above steps, after obtaining the bullet likelihood of each pixel point, compare the bullet likelihoods of all pixel points with this preset infrared threshold. If the bullet likelihood of a certain pixel point is greater than this threshold, it is considered that this pixel point is the pixel point of the bullet, and it is used as a suspected bullet pixel point for subsequent processing. In an embodiment of the present invention, the preset infrared threshold is 0.37, which is used to distinguish suspected bullet pixel points and background pixel points. This threshold is determined based on experimental data or experience, and the implementer can set it according to the implementation scenario.

[0055] To preliminarily determine the corresponding area of the bullet, preferably, in an embodiment of the present invention, the method for obtaining the suspected bullet area includes:

[0056] Using the connected component analysis method, determine each connected component according to all suspected bullet pixel points in the initial infrared image of the bullet; perform morphological operations on each connected component to obtain each suspected bullet area in the initial infrared image of the bullet. It should be noted that the connected component analysis method and morphological operations are well-known prior arts to those skilled in the art and will not be elaborated here.

[0057] For the above steps, the purpose of the connected component analysis method is to group adjacent suspected bullet pixel points in the initial infrared imaging of the bullet to form each connected region. Each connected component corresponds to a potential bullet region; after obtaining each connected component, morphological operations need to be performed on each connected component next. Morphological operations are a set of image processing techniques based on the shape of the image, including dilation, erosion, opening operation, and closing operation, etc. The purpose of morphological operations is to adjust and optimize the shape of the connected component. For example, through the dilation operation, the void points or fine cracks inside the connected component can be filled; through the erosion operation, the fine protrusions or noise points on the edge of the connected component can be removed; through the opening operation, small objects can be removed while keeping the shape of larger objects unchanged; through the closing operation, the small holes inside the object can be filled while smoothing its boundary. By these operations, each suspected bullet region can be obtained, making the suspected bullet region more complete and facilitating subsequent identification and extraction.

[0058] Considering the interference of the thermal radiation of background objects, non-bullet regions may be wrongly identified as suspected bullet regions. By comparing the similarity between the shape of the suspected region and the preset standard bullet shape, the misdetected regions corresponding to the background objects can be more effectively excluded, thereby improving the accuracy of identifying the real bullet region. Preferably, in an embodiment of the present invention, the method for obtaining the real bullet region includes:

[0059] Taking the suspected bullet region and the preset standard bullet as the regions to be measured respectively; calculating the cumulative value of the curvature values corresponding to all feature points on the edge of the region to be measured as the shape curvature value of the region to be measured; calculating the absolute value of the difference between the shape curvature values of the suspected bullet region and the preset standard bullet and performing a negative correlation mapping to obtain the real possibility of each suspected bullet region;

[0060] Taking the suspected bullet region corresponding to the maximum real possibility as the real bullet region. It should be noted that the methods for obtaining the edge, curvature value, and feature points are well-known prior arts to those skilled in the art. The edge can be extracted through an edge detection algorithm, the curvature value can be obtained by the least squares method, and the feature points can be obtained by SIFT corner detection, which will not be elaborated here. The preset standard bullet in the present invention is based on the standard shape of the target bullet, and the implementer can set it according to the implementation scenario, which is not limited here. The negative correlation mapping in the present invention can adopt the form of inverse proportion or negative exponential power, which is not limited here.

[0061] For the above steps, the suspected bullet area and the preset standard bullet are used as the areas to be measured respectively. For each area to be measured, the cumulative value of the curvature values corresponding to all feature points on its edge is calculated as the shape curvature value of the area to be measured. The curvature value reflects the degree of bending of the edge and is an important feature in shape analysis. Calculate the absolute value of the difference between the shape curvature values of the suspected bullet area and the preset standard bullet, and perform a negative correlation mapping to obtain the true possibility of each suspected bullet area. Negative correlation mapping means that the smaller the difference, that is, the more similar the shapes, the higher the obtained true possibility. In this way, each suspected bullet area will obtain a true possibility value related to its shape similarity. Since there is only one bullet in the initial infrared imaging of the bullet in this scenario, the suspected bullet area with the maximum true possibility is determined as the true bullet area, and the true bullet area can more accurately reflect the area corresponding to the true bullet.

[0062] When dealing with the problem of the initial infrared imaging of a bullet during its flight, due to the complex environment, tiny particles are likely to adhere to the bullet surface, and these particles will significantly affect the accurate capture of the actual infrared radiation characteristics of the bullet by the infrared imaging device. To address this issue, measures are needed to correct this inaccurate infrared radiation value and finally generate an infrared image simulation model that can reflect the true infrared characteristics of the bullet.

[0063] Step S3: According to the infrared radiation values of the pixel points in the true bullet area, screen out each pixel point to be corrected; according to the infrared radiation values in the local area of the pixel point to be corrected, obtain the corrected infrared radiation value of the pixel point to be corrected; according to the corrected infrared radiation values of all pixel points to be corrected, correct the initial infrared imaging of the bullet to obtain the corrected infrared imaging of the bullet; generate an infrared image simulation model based on the corrected infrared imaging of the bullet.

[0064] Considering the influence of particulate matter on the bullet, according to the infrared radiation value situation of the pixel points in the true bullet area, screen out the pixel points to be corrected caused by the influence of tiny particles. For the screened pixel points to be corrected, it is necessary to obtain their corrected infrared radiation values according to the infrared radiation values in the local area of these pixel points to make them closer to the true values. After obtaining the corrected infrared radiation values of all pixel points to be corrected, the initial infrared imaging of the bullet can be corrected as a whole, so that the corrected infrared imaging of the bullet can more accurately reflect the actual infrared radiation characteristics of the bullet, thereby improving the accuracy of the generated infrared image simulation model.

[0065] To determine the pixel points affected by particulate matter in the initial infrared imaging of the bullet, please refer to Figure 3 , which shows a flowchart of a method for obtaining pixel points to be corrected in an embodiment of the present invention. Preferably, in an embodiment of the present invention, the method for obtaining pixel points to be corrected includes:

[0066] Step S301: Obtain the first influence degree of particulate matter in the real bullet area according to the direction characteristics of the real bullet area.

[0067] To evaluate the influence degree of the real bullet area by particulate matter, the first influence degree of particulate matter is obtained by analyzing the influence of the angle between the bullet flight direction and the gravity direction on the adhesion of particulate matter.

[0068] Preferably, in an embodiment of the present invention, the method for obtaining the first influence degree of particulate matter includes:

[0069] Using the principal component analysis method, the main direction of the real bullet area is used as the flight direction of the real bullet area; the direction perpendicular to the ground is used as the reference direction; the included angle value between the flight direction and the reference direction is negatively correlated and mapped to obtain the first influence degree of particulate matter in the real bullet area. It should be noted that extracting the main direction using the principal component analysis method is a well-known prior art to those skilled in the art and will not be elaborated here.

[0070] For the above steps, the principal component analysis method is used to analyze the direction characteristics of the real bullet area, and the main flight direction of the bullet is extracted. The principal component analysis method is a statistical method used to identify the principal components in the real bullet area and is used here to determine the flight direction of the bullet. The direction perpendicular to the ground is defined as the reference direction. This is to quantify the angle between the flight direction and the gravity direction, because gravity is an important factor affecting the adhesion of particulate matter, and the included angle value between the bullet flight direction and the reference direction is calculated. This included angle value reflects the relative positional relationship between the bullet flight direction and the gravity direction. The included angle value is negatively correlated and mapped to obtain the first influence degree of particulate matter. The higher the first influence degree of particulate matter, the closer the bullet flight direction is to vertically downward, the more gravity helps the adhesion of dust particles, and the greater the influence degree of the real bullet area by particulate matter.

[0071] In other embodiments of the present invention, the method for obtaining the first influence degree of particulate matter includes:

[0072] Among the edges of the area to be analyzed, each straight line segment is identified; the longest straight line segment is used as the main extension line segment of the bullet; the straight line perpendicular to the ground is used as the reference straight line; the included angle value between the main extension line segment of the bullet and the reference straight line is negatively correlated and mapped to obtain the first influence degree of particulate matter in the real bullet area. It should be noted that the methods for obtaining the edge and the straight line segment are well-known prior arts to those skilled in the art and will not be elaborated here. The edge of the area to be analyzed can be extracted by an edge detection algorithm, and each straight line segment can be identified using the Hough transform algorithm. The negative correlation mapping of the present invention can adopt the form of inverse proportion or negative exponential power and is not limited here.

[0073] Regarding the above steps, the straight line segment reflects the main part of the bullet contour. The longest straight line segment is selected as the main extension line segment of the bullet. This line segment best represents the flying direction of the bullet. The straight line perpendicular to the ground is defined as the reference line. In the image coordinate system of the present invention, the Y-axis represents the straight line perpendicular to the ground, that is, the Y-axis is used as the reference line, and the included angle value between the main extension line segment of the bullet and the reference line is calculated. This included angle value reflects the relative positional relationship between the flying direction of the bullet and the vertical direction of the ground. When the included angle value is smaller, that is, the bullet is closer to flying vertically downward, gravity is more conducive to the attachment of dust particles, so the first influence degree of the particulate matter is higher.

[0074] Step S302: Obtain the second influence degree of the particulate matter of the pixel point according to the difference between the infrared radiation value of the pixel point and its local infrared radiation value.

[0075] By constructing the second influence degree of the particulate matter, the degree to which the pixel point is affected by the particulate matter is evaluated.

[0076] Preferably, in an embodiment of the present invention, the method for obtaining the second influence degree of the particulate matter includes:

[0077] In the flying direction, the average value of the corresponding infrared radiation values of the previous pixel point and the next pixel point of the pixel point is used as the local infrared radiation value of the pixel point; the absolute value of the difference between the infrared radiation value of the pixel point and the local infrared radiation value is calculated to obtain the second influence degree of the particulate matter of the pixel point.

[0078] Regarding the above steps, in the flying direction of the bullet, for each pixel point, its previous pixel point and the next pixel point are selected. The average value of the corresponding infrared radiation values of these two adjacent pixel points is calculated as the local infrared radiation value of the current pixel point. The absolute value of the difference between the infrared radiation value of the current pixel point and the local infrared radiation value is calculated to obtain the second influence degree of the particulate matter of the pixel point. The greater the second influence degree of the particulate matter, the greater the difference between the infrared radiation value of the current pixel point and the local area, and the more likely it is to be significantly affected by the particulate matter.

[0079] Step S303: Positively fuse the first influence degree of the particulate matter corresponding to the pixel point and the second influence degree of the particulate matter to obtain the comprehensive influence degree of the particulate matter of the pixel point.

[0080] By constructing the comprehensive influence degree of the particulate matter, the degree to which the pixel point is affected by the particulate matter is comprehensively evaluated.

[0081] It should be noted that forward fusion is an existing technology well-known to those skilled in the art. Forward fusion can adopt simple multiplication, arithmetic mean or other suitable fusion methods. In an embodiment of the present invention, the product of the first influence degree of the particulate matter corresponding to the pixel point and the second influence degree of the particulate matter is calculated and normalized to obtain the comprehensive influence degree of the particulate matter of the pixel point. It should be noted that the normalization method adopted is: using the norm normalization function for normalization, and restricting the numerical range between 0 and 1. Among them, normalization is a technical means well-known to those skilled in the art, and the choice of the normalization function can be linear normalization or standard normalization, etc. The specific normalization method is not limited herein.

[0082] For the above steps, considering each pixel point, calculate the product of the corresponding first influence degree of the particulate matter and the second influence degree of the particulate matter. This product reflects the combined effect between the two influence degrees, that is, when both are relatively high, the product will also be high, indicating that the pixel point is more affected by the particulate matter. The value after normalization is used as the comprehensive influence degree of the particulate matter of the pixel point. The greater the comprehensive influence degree of the particulate matter, the higher the degree to which the pixel point is affected by the particulate matter.

[0083] Step S304: According to the comprehensive influence degree of the particulate matter, screen out each pixel point to be corrected from all pixel points in the real bullet area.

[0084] Based on the comprehensive influence degree of the particulate matter, identify those pixel points in the real bullet area that are more affected by the particulate matter and mark them as pixel points to be corrected. These pixel points to be corrected will have their infrared radiation values corrected in subsequent steps.

[0085] Preferably, in an embodiment of the present invention, the method for screening out each pixel point to be corrected includes:

[0086] In the real bullet area, mark each pixel point whose comprehensive influence degree of the particulate matter is greater than the preset particulate matter influence threshold as each pixel point to be corrected. In an embodiment of the present invention, the preset particulate matter influence threshold is 0.47, and the implementer can set it according to the implementation scenario.

[0087] For the above steps, the preset particulate matter influence threshold is used to determine whether a pixel point is affected by a large enough amount of particulate matter and thus needs to be marked as a pixel point to be corrected. In the real bullet area, traverse all pixel points and check their comprehensive influence degrees of the particulate matter. For pixel points whose comprehensive influence degree of the particulate matter is greater than the preset particulate matter influence threshold, mark them as pixel points to be corrected. These pixel points are considered areas more affected by the particulate matter and need to have their infrared radiation values corrected.

[0088] To determine the infrared radiation value of the pixel to be corrected that is closer to the actual infrared radiation characteristics of the bullet, preferably, in an embodiment of the present invention, the method for obtaining the corrected infrared radiation value includes:

[0089] In the preset local area of the pixel to be corrected, each pixel except the pixel to be corrected is used as a reference pixel; the average value of the infrared radiation values of all reference pixels is calculated and used as the corrected infrared radiation value of the pixel to be corrected. In an embodiment of the present invention, with the pixel as the central pixel, a preset local area of size 3 × 3 is constructed, and the center of the preset local area is the central pixel.

[0090] For the above steps, calculate the average value of the infrared radiation values of all reference pixels. This average value reflects the average infrared radiation characteristics of the local area around the pixel to be corrected. The calculated average value of the infrared radiation value is used as the corrected infrared radiation value of the pixel to be corrected. This value is used to replace the infrared radiation value of the pixel to be corrected in the original infrared imaging, so that it is closer to the actual infrared radiation characteristics of the bullet.

[0091] To make the corrected infrared imaging of the bullet more accurately reflect the actual infrared radiation characteristics of the bullet, preferably, in an embodiment of the present invention, the method for obtaining the corrected infrared imaging of the bullet includes:

[0092] Replace the corrected infrared radiation value of the pixel to be corrected with the infrared radiation value at the corresponding pixel position in the initial infrared imaging of the bullet to obtain the corrected infrared imaging of the bullet.

[0093] For the above steps, in the initial infrared imaging of the bullet, find the pixel corresponding to the position of the pixel to be corrected, and replace its original infrared radiation value with the corrected infrared radiation value calculated above. After traversing all the pixels to be corrected and completing the replacement of the infrared radiation values, a more accurate corrected infrared imaging of the bullet can be obtained.

[0094] After establishing the correlation between the surface temperature of the object and the infrared radiation value, the next step is to generate a realistic infrared image simulation model. It should be noted that the method for constructing the infrared image simulation model is a well-known prior art to those skilled in the art. Here, a simple description is given of generating an infrared image simulation model based on the corrected infrared imaging of the bullet: Parameter fine-tuning: The initially drawn corrected infrared imaging of the bullet may still need to be fine-tuned to make it more realistic. This includes adjusting parameters such as the brightness, contrast, and color of the image, as well as considering the influence of environmental factors such as atmospheric attenuation and background radiation on the corrected infrared imaging of the bullet. Model verification: Finally, it is necessary to verify the generated infrared image simulation model of the corrected infrared imaging of the bullet. This is usually done by comparing it with the actual infrared imaging results to ensure the accuracy and reliability of the infrared image simulation model.

[0095] The present invention provides an infrared imaging simulation system based on data analysis, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of an infrared imaging simulation method based on data analysis are implemented.

[0096] In summary, the embodiments of the present invention provide an infrared imaging simulation method and system based on data analysis. First, according to the difference in the infrared radiation values of pixel points in the initial infrared imaging of the bullet, each suspected bullet pixel point is screened out from all pixel points; according to the infrared radiation values of pixel points in the real bullet area, each pixel point to be corrected is screened out; according to the infrared radiation values in the local area of the pixel point to be corrected, the corrected infrared radiation value of the pixel point to be corrected is obtained; according to the corrected infrared radiation values of all pixel points to be corrected, the initial infrared imaging of the bullet is corrected to obtain the corrected infrared imaging of the bullet; according to the corrected infrared imaging of the bullet, an infrared image simulation model is generated. By deeply analyzing the influence of particulate matter on the infrared radiation value, the present invention constructs a corrected infrared imaging of the bullet to more accurately reflect the actual infrared radiation characteristics of the bullet, thereby improving the accuracy of the generated infrared image simulation model.

[0097] It should be noted that the above sequence of embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0098] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. An infrared imaging simulation method based on data analysis, characterized in that: The method comprises: Acquire the initial infrared imaging of the bullet during its flight; According to the difference of the infrared radiation values ​​of the pixels in the initial infrared imaging of the bullet, each suspected bullet pixel is screened out from all the pixels; according to all the suspected bullet pixels in the initial infrared imaging of the bullet, each suspected bullet area is determined; according to the deviation of the suspected bullet area from the standard, the real bullet area is screened out; According to the infrared radiation values ​​of the pixels in the real bullet area, each pixel to be corrected is screened out; according to the infrared radiation values ​​in the local area of ​​the pixel to be corrected, the corrected infrared radiation values ​​of the pixel to be corrected are obtained; according to the corrected infrared radiation values ​​of all the pixels to be corrected, the initial infrared imaging of the bullet is corrected to obtain the corrected infrared imaging of the bullet; according to the corrected infrared imaging of the bullet, an infrared image simulation model is generated; The method for obtaining the real bullet area comprises: The suspected bullet area and the preset standard bullet are respectively used as the test area; the cumulative value of the curvature values ​​corresponding to all feature points on the edge of the test area is calculated as the shape curvature value of the test area; the absolute value of the difference between the shape curvature values ​​of the suspected bullet area and the preset standard bullet is calculated and negatively correlated to obtain the true possibility of the suspected bullet area; The maximum true possibility is corresponded to the suspected bullet area as the real bullet area.

2. The infrared imaging simulation method based on data analysis according to claim 1, characterized in that: The method for obtaining the suspected bullet pixel point comprises: In the initial infrared imaging of the bullet, the bullet probability of the pixel point is obtained according to the difference between the infrared radiation value of the pixel point and the overall infrared radiation value of the initial infrared imaging of the bullet; Each pixel point whose bullet possibility is greater than a preset infrared threshold is marked as each suspected bullet pixel point.

3. The infrared imaging simulation method based on data analysis according to claim 2, characterized in that: The method for obtaining the bullet probability includes: The average of the infrared radiation values ​​corresponding to all pixels in the initial infrared imaging of the bullet is calculated to obtain the overall infrared radiation value of the initial infrared imaging of the bullet; the difference between the infrared radiation value of the pixel and the overall infrared radiation value is calculated and normalized to obtain the bullet probability of the pixel.

4. The infrared imaging simulation method based on data analysis according to claim 1, characterized in that: The method for obtaining the pixel to be corrected comprises: According to the directional characteristics of the real bullet area, obtaining a first influence degree of particles in the real bullet area; Obtaining a second influence degree of the particulate matter at the pixel point according to a difference between the infrared radiation value of the pixel point and its local infrared radiation value; Forward fusion of the first influence degree of the particle corresponding to the pixel point and the second influence degree of the particle point to obtain the comprehensive influence degree of the particle at the pixel point; According to the comprehensive influence of the particles, each pixel point to be corrected is selected from all the pixel points in the real bullet area.

5. The infrared imaging simulation method based on data analysis according to claim 4, characterized in that: The method for obtaining the first impact degree of the particulate matter includes: Using the principal component analysis method, the main direction of the real bullet area is taken as the flight direction of the real bullet area; the vertical ground direction is taken as the reference direction; the angle value between the flight direction and the reference direction is negatively correlated to obtain the first influence degree of the particles in the real bullet area.

6. The infrared imaging simulation method based on data analysis according to claim 5, characterized in that: The method for obtaining the second influence degree of the particulate matter includes: In the flight direction, the average of the infrared radiation values ​​corresponding to the previous pixel and the next pixel of the pixel is taken as the local infrared radiation value of the pixel; the absolute value of the difference between the infrared radiation value of the pixel and the local infrared radiation value is calculated to obtain the second influence degree of the particle matter of the pixel.

7. The infrared imaging simulation method based on data analysis according to claim 4, characterized in that: The method for obtaining the comprehensive impact of particulate matter includes: The product of the first influence degree of the particle corresponding to the pixel point and the second influence degree of the particle point is calculated and normalized to obtain the comprehensive influence degree of the particle point.

8. The infrared imaging simulation method based on data analysis according to claim 1, characterized in that: The method for obtaining the corrected infrared radiation value includes: In a preset local area of ​​the pixel to be corrected, each pixel except the pixel to be corrected is used as a reference pixel; and the average of the infrared radiation values ​​of all reference pixels is calculated as the corrected infrared radiation value of the pixel to be corrected.

9. An infrared imaging simulation system based on data analysis, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the infrared imaging simulation method based on data analysis as described in any one of claims 1 to 8 are implemented.

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