Method and device for generating whole infrared image of moving target containing exhaust smoke plume

Abstract

The invention discloses a method and a device for generating an integral infrared image of a moving target containing exhaust smoke plume. The method comprises the steps of generating a first infrared image of a target solid wall surface at a current moment based on detection information at the current moment and a pre-constructed target geometric grid model; calculating a first distance from each pixel in the first infrared image to the detector; based on the detection angle, determining a second smoke plume image consistent with the detection angle at the current moment from a predetermined multi-angle exhaust smoke plume infrared radiation sequence image; synthesizing the first infrared image and the second smoke plume image to generate an initial overall infrared image at the current moment; calculating a second distance from each pixel in the initial integral infrared image to the detector; and based on the relationship between each first distance and each second distance, assigning a value to each pixel in the initial overall infrared image, and generating a final overall infrared image at the current moment. According to the invention, the overall infrared image of the moving target can be quickly and accurately generated.

Description

Technical Field

[0001] The present invention relates to the field of infrared simulation technology, and in particular to a method and a device for generating an overall infrared image of a moving target including an exhaust plume. Background Art

[0002] The overall infrared radiation of the target including the exhaust plume mainly includes the spontaneous radiation of the solid wall of the target and the scattering of the ambient radiation, as well as the infrared radiation of the exhaust plume generated by the power system such as combustion. Among them, the infrared radiation characteristics of the exhaust plume are the most significant, especially when detecting in medium wave, which can reach more than 46% of the overall infrared radiation of the target.

[0003] In the related art, when the target is stationary, the infrared radiation three-dimensional model of the target solid wall and the infrared radiation two-dimensional image of the exhaust plume can be generated respectively, and the two can be simply superimposed to obtain the overall infrared image of the target. However, when the target and the detector are in motion, the detection information (such as the detection angle and detection distance, etc.) will change in real time. At this time, it is necessary to consider the imaging changes of the target solid wall and the exhaust plume at different times and the occlusion relationship between the two. The existing method cannot meet the demand for rapid generation of the overall infrared radiation image of the moving target in dynamic scenes.

[0004] Therefore, there is an urgent need for a method and device for generating an overall infrared image of a moving target including an exhaust plume to solve the above-mentioned problem. Summary of the invention

[0005] The present invention provides a method and device for generating an overall infrared image of a moving target including an exhaust plume, which can quickly and accurately generate an overall infrared image of the moving target. The technical solution is as follows:

[0006] In one aspect, a method for generating an overall infrared image of a moving target including an exhaust plume is provided, the method comprising:

[0007] Based on the detection information at the current moment and the pre-constructed target geometric grid model, a first infrared image of the target solid wall at the current moment is generated; the detection information includes the detection position, detection angle and detection resolution of the detector;

[0008] Calculating a first distance from each pixel in the first infrared image to the detector;

[0009] Based on the detection angle, determining a second smoke plume image consistent with the detection angle at the current moment from a predetermined multi-angle exhaust smoke plume infrared radiation sequence image;

[0010] Synthesize the first infrared image and the second smoke plume image to generate an initial overall infrared image at the current moment;

[0011] Calculating a second distance from each pixel in the initial overall infrared image to the detector;

[0012] Based on the relationship between each of the first distances and each of the second distances, a value is assigned to each pixel in the initial overall infrared image to generate a final overall infrared image at the current moment.

[0013] In another aspect, a device for generating an overall infrared image of a moving target including an exhaust plume is provided, the device comprising:

[0014] A first generating unit is used to generate a first infrared image of the target solid wall at the current moment based on the detection information at the current moment and a pre-constructed target geometric grid model; the detection information includes a detection position, a detection angle and a detection resolution of the detector;

[0015] A first calculation unit, used for calculating a first distance from each pixel in the first infrared image to the detector;

[0016] A determination unit, configured to determine, based on the detection angle, a second smoke plume image consistent with the detection angle at a current moment from a predetermined multi-angle exhaust smoke plume infrared radiation sequence image;

[0017] A second generating unit, configured to synthesize the first infrared image and the second smoke plume image to generate an initial overall infrared image at a current moment;

[0018] A second calculation unit, used for calculating a second distance from each pixel in the initial overall infrared image to the detector;

[0019] The third generating unit is used to assign a value to each pixel in the initial overall infrared image based on the relationship between each of the first distances and each of the second distances, so as to generate a final overall infrared image at a current moment.

[0020] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored in the storage medium, and when the computer program is executed by a processor, the steps of the above-mentioned method for generating an overall infrared image of a moving target including an exhaust plume are implemented.

[0021] On the other hand, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of the above-mentioned method for generating an overall infrared image of a moving target including an exhaust plume.

[0022] The embodiment of the present invention provides a method for generating an overall infrared image of a moving target including an exhaust plume. The first infrared image of the target solid wall is calculated through the parallel accelerated computing capability of the rendering engine in the GPU, and the detection distance information of each pixel in the image, that is, the first distance, is simultaneously solved. Then, the corresponding second plume image is determined based on the detection angle, and the two images are synthesized to obtain an initial overall infrared image. Then, according to the exit position and smoke emission direction of the target plume, the second distance from each pixel in the initial overall infrared image to the detector is calculated; finally, when assigning values ​​to the pixels in the initial overall infrared image, the occlusion relationship between the pixels is judged according to the first distance and second distance information of each pixel, and each pixel is assigned a value according to the judgment result to obtain the final overall infrared image. It can be seen that the present application can quickly synthesize the three-dimensional radiation model of the target solid wall and the two-dimensional radiation model of the exhaust plume, and quickly generate an infrared sequence image under the dynamic trajectory of the infrared detector. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 creative work.

[0024] Figure 1 It is a flow chart of a method for generating an overall infrared image of a moving target including an exhaust plume provided by one embodiment of the present invention;

[0025] Figure 2 It is a structural diagram of a device for generating an overall infrared image of a moving target including an exhaust plume provided by one embodiment of the present invention;

[0026] Figure 3 is a hardware architecture diagram of a computer device provided by an embodiment of the present invention;

[0027] Figure 4 is a schematic diagram of detection imaging of a target solid wall provided by an embodiment of the present invention;

[0028] Figure 5 This is a schematic diagram of a sequence of infrared radiation images of exhaust plumes from multiple angles provided by an embodiment of the present invention;

[0029] Figure 6 to Figure 8 They are schematic diagrams of overall infrared image sequences generated at different times and different detection angles using the method of the present application. DETAILED DESCRIPTION

[0030] 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, rather than all the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0031] The specific implementation of the above concept is described below.

[0032] Please refer to Figure 1 , an embodiment of the present invention provides a method for generating an overall infrared image of a moving target including an exhaust plume, the method comprising:

[0033] Step 100, based on the detection information at the current moment and the pre-built target geometric grid model, a first infrared image of the target solid wall at the current moment is generated; the detection information includes the detection position, detection angle and detection resolution of the detector;

[0034] Step 102, calculating a first distance from each pixel in the first infrared image to the detector;

[0035] Step 104, based on the detection angle, determining a second smoke plume image consistent with the current detection angle from the predetermined multi-angle exhaust smoke plume infrared radiation sequence image;

[0036] Step 106, synthesizing the first infrared image and the second smoke plume image to generate an initial overall infrared image at the current moment;

[0037] Step 108, calculating a second distance from each pixel in the initial overall infrared image to the detector;

[0038] Step 110 , assigning a value to each pixel in the initial overall infrared image based on the relationship between each first distance and each second distance, to generate a final overall infrared image at the current moment.

[0039] In this embodiment, the first infrared image of the target solid wall is calculated through the parallel accelerated computing capability of the rendering engine in the GPU, and the detection distance information of each pixel in the image, that is, the first distance, is solved synchronously. Then, the corresponding second plume image is determined based on the detection angle, and the two images are synthesized to obtain an initial overall infrared image. Then, according to the exit position and smoke direction of the target plume, the second distance from each pixel in the initial overall infrared image to the detector is calculated; finally, when assigning values ​​to the pixels in the initial overall infrared image, the occlusion relationship between the pixels is judged according to the first distance and second distance information of each pixel, and each pixel is assigned a value according to the judgment result to obtain the final overall infrared image. It can be seen that the present application can quickly synthesize the three-dimensional radiation model of the target solid wall and the two-dimensional radiation model of the exhaust plume, and quickly generate infrared sequence images under the dynamic trajectory of the infrared detector.

[0040] Described below Figure 1 How the various steps are performed.

[0041] First, step 100 includes:

[0042] Perform polynomial fitting on the Planck formula of the object's own infrared radiation to obtain the first formula for calculating the radiation brightness of the object itself within a preset band;

[0043] Based on the current observation angle, the normal vector of each facet vertex in the grid model, and the temperature and emissivity of the target solid wall, the infrared radiation brightness value of each vertex is calculated using the first formula;

[0044] Based on the BRDF parameters of each face element in the mesh model, the reflected ambient infrared radiation brightness value of each face element vertex is calculated;

[0045] Based on the infrared radiation brightness value of each vertex and the infrared radiation brightness value of the reflected environment, a first infrared image of the target solid wall surface at the current moment is generated.

[0046] In this embodiment, according to infrared radiation theory, without considering atmospheric transmission, infrared radiation consists of two parts: the infrared radiation of the object itself and the infrared radiation of the reflected environment. For example, at the surface M of the object, in the observation direction (θ out ,φ out ) at which the object receives the total infrared radiation L out (T,M,θ out ,φ out ,λ i )for:

[0047] L out (T,M,θ out ,φ out ,λi )=L e (T,M,θ out ,φ out ,λ i )+L r (M,θ out ,φ out ,λ i ) (1)

[0048] Where T is the surface temperature of the object, L e (T,M,θ out ,φ out ,λ i ) is the object surface M in the observation direction (θ out ,φ out ) at its own infrared radiation brightness, (W / (m 2 ·sr));L r (M,θ out ,φ out ,λ i ) is the object surface M in the observation direction (θ out ,φ out ) is the reflected ambient radiation brightness, (W / (m 2 ·sr)).

[0049] The following are two ways to calculate infrared radiation:

[0050] (1) Calculation of the object's own infrared radiation

[0051] The infrared radiation of the object itself satisfies Planck's formula. The calculation formula for the radiation brightness of the solid target itself within the band λ1 to λ2 is:

[0052]

[0053] Among them, λ2 and λ1 are the upper and lower limits of the infrared band, μm; ε(λ,T) is the reflectivity of the object, which is a function of temperature and wavelength; C1 is the first radiation constant, C1=3.7419×10 -16 W·m 2 , C2 is the second radiation constant, C2=1.4388×10 - 2 m.K.

[0054] From formula (2), it can be seen that the calculation of the radiation of solid targets in any band needs to be integrated. The detection imaging under the dynamic trajectory of the infrared detector cannot meet the real-time requirements, so a polynomial approximation method is needed for fitting calculation. This application uses a fourth-order polynomial fitting. After fitting, the first formula for calculating the radiation brightness of the object itself in the preset band is:

[0055] L e (T,M,θ out ,φ out ,λ1-λ2)=(a0+a1T+a2T 2 +a3T 3 +a4T 4 +…)·ε·(1-(1-cosθ) 5 ) (3)

[0056] Among them, ε is the material emissivity, θ is the angle between the observation angle and the normal of the object surface; the coefficients a0, a1, a2, a3, and a4 are obtained by least squares fitting and uniquely correspond to the calculated band λ1 to λ2.

[0057] After comparing the errors of the fitting calculation, the 4th-order polynomial fitting is used in the simulation process, and the error is less than 0.01% compared with the calculation result of Planck integral formula (1), which meets the actual simulation accuracy requirements. It should be noted that customers can also perform higher-order fitting according to actual needs, and this application does not specifically limit its order.

[0058] (2) Calculation of environmental radiation reflected by objects

[0059] The object-reflected ambient radiation includes the specular reflection and diffuse reflection of the object surface. Therefore, the object-reflected ambient radiation can be expressed by the following formula:

[0060]

[0061] Among them, Ω represents the hemispherical space where point M on the surface of the object is located, ω∈Ω; f r (M,θ in ,φ in ,θ out ,φ out ) is the bidirectional reflection function at M; L ΔΩ (M,θ in ,φ in ,λ1-λ2) is in a specific wavelength range and the incident direction is (θ in ,φ in ), the incident radiance at M is (W / (m 2 ·sr)).

[0062] The reflected radiation of an object mainly includes the reflection of the sky environment background radiation and the reflection of solar radiation by the object surface. When calculating the reflected radiation, the contribution of all radiation sources in the hemispherical space Ω needs to be considered.

[0063] Therefore, the ambient radiation reflected by an object can be expressed as follows:

[0064]

[0065] Among them, ρ d (M,θ out ,φ out ) is the diffuse reflection coefficient of the object; E env (M,λ1-λ2) is the hemispherical sky environment radiation received by point M on the surface of the object within a specific wavelength range, E env (M,λ1-λ2)=∫ Ω L env (θ i )cosθ i dω,W·m 2 ; L env (θ i ) is the detection angle θ i The ambient radiance under i is any angle in the detection hemisphere space; f r (M,θ sun ,φ sun ,θ out ,φ out ) is the reflection coefficient of solar radiation in a single direction, θ sun ,φ sun are the azimuth and elevation angles of the sun’s rays; E sun (M,λ1-λ2) is the solar radiation received by point M on the surface of the object within a specific wavelength range.

[0066] Since real objects have a certain degree of roughness, their reflection characteristics are between diffuse reflection and specular reflection, and have a certain directionality. Therefore, in order to accurately describe the directionality of the reflection characteristics of the object surface, the bidirectional reflectance distribution function (BRDF) is used to characterize the reflection coefficient f r (M,θ sun ,φ sun ,θ out ,φ out ). The typical Cook-Torrance BRDF model is used for calculation, and the model is defined as follows:

[0067] f r (M,θ sun ,φ sun ,θ out ,φ out ) = k d ·f lambert +k s ·f cook-torrance (6)

[0068] Among them, k d , k s The proportion of energy refracted and the proportion of energy reflected (generally determined by the Fresnel term), and flambert Refers to the diffuse BRDF, f cook-torrance Refers to the BRDF of specular reflection.

[0069] Substituting equation (6) into equation (5), we can get the brightness value of ambient infrared radiation reflected by the object.

[0070] It should be noted that since the target geometric network model is composed of multiple face elements, each face element has multiple vertices. Therefore, as long as the infrared radiation brightness value of each vertex itself and the reflected ambient infrared radiation brightness value are calculated and superimposed, the first infrared image of the target solid wall at any time can be obtained.

[0071] In addition, this application uses the target solid wall temperature and emissivity data as input to carry out infrared radiation brightness calculation of solid targets. The infrared image calculation process is based on GPU acceleration technology, which utilizes the characteristics of multi-core and dedicated memory structure and can provide higher computing efficiency when processing large-scale parallel computing tasks.

[0072] With respect to step 102, calculating a first distance from each pixel in the first infrared image to the detector includes:

[0073] For each pixel in the first infrared image, perform:

[0074] Determine the number of vertices contained in the pixel;

[0075] For each vertex contained in the pixel, the following operations are performed: based on the vector from the detector to the vertex and the vector from the detector to the target center, the difference between the distance from the vertex to the detector and the distance from the target center to the detector is calculated; in the GPU shader, the distance difference is written into the transparency channel of the vertex color to obtain the channel value of the vertex;

[0076] The average value of the channel value of each vertex is taken as the channel value of the pixel;

[0077] Based on the channel value of the pixel, a first distance from the pixel to the detector is calculated.

[0078] In this step, the first infrared image is denoted as M1, and the number of pixels of the image is X1×Y1, 1≤m≤X1, 1≤n≤Y1, where X1 and Y1 are the number of horizontal and vertical pixels of the image M1 respectively. A pixel can contain multiple vertices, denoted as S j (s jx ,s jy ,s jz ).

[0079] Assume the position of the detector is R(r x ,r y ,r z), based on the rendering engine, automatically obtain the vector from the detector position to the target center coordinate O(0,0,0) Get the detector position to each vertex S j (s jx ,s jy ,s jz ) Then the distance difference E between each vertex and the detector and the distance from the target center O(0,0,0) to the detector is calculated. j , the calculation formula is as follows:

[0080]

[0081] in, Represents vector and Length.

[0082] In the GPU shader, the distance difference E j Write the A channel (i.e. transparency channel) of each vertex color. Assume that the model length is L (L is less than 200m). To ensure that the color channel value is between 0 and 1, the A channel value of each vertex is designed as follows:

[0083]

[0084] Then the channel value of the mn-th pixel in the first image is:

[0085]

[0086] The first distance calculation formula from the mnth pixel in the first image to the detector is:

[0087]

[0088] Where, L mn is the first distance from the mnth pixel in the first image to the detector; A mn is the channel value of the mnth pixel in the first image; A j and E j are the channel value of the jth vertex in the mnth pixel, the distance between the jth vertex and the detector, and the distance between the target center and the detector, j = 1, 2...K, K is the number of vertices contained in the mnth pixel; L is the length of the grid model; is the vector from the detector to the jth vertex; is the vector from the detector to the center of the target.

[0089] In addition, in the first infrared image M1, set g as the camera angular resolution (unit radian), then the spatial resolution R corresponding to each pixel in M1 is 1mn (Unit: meter) is:

[0090] R 1mn = g·L mn (11)

[0091] With respect to step 104, since the infrared radiation sequence images of the exhaust plume at multiple angles have been predetermined, it is only necessary to determine the detection angle to query the second plume image that is consistent with the detection angle at the current moment.

[0092] With respect to step 106, the first infrared image and the second smoke plume image are synthesized to generate an initial overall infrared image at the current moment, including:

[0093] The resolutions of the first infrared image and the second smoke plume image are uniformly converted based on the UV coordinates to obtain an image with uniform resolution;

[0094] For the images with unified resolution, the center position of the chimney outlet in the first infrared image and the center of the plume bottom in the second plume image are taken as the coincidence points of the two images. The first infrared image is superimposed on the second plume image to generate the initial overall infrared image at the current moment.

[0095] In this step, the second plume image is recorded as M2, the number of image pixels is X2×Y2, X2 and Y2 are the horizontal and vertical pixel numbers of image M2 respectively, and the image spatial resolution is R 2mn (Unit: meter). The overall infrared image ultimately needs to be synthesized by using the same resolution to combine the image M1 and the image M2 at the same viewing angle. Considering that the smoke plume may be blocked by the solid part of the target in some detection directions, the blocking relationship is determined by the distance information of the first infrared image and the second smoke plume image relative to the detector, so as to perform the synthesis calculation.

[0096] (1) Uniform conversion of image resolution based on UV coordinates.

[0097] The UV coordinates in the rendering engine are normalized rectangular coordinates. Therefore, in order to facilitate the unification of image resolution, the coordinates of images M1 and M2 are normalized to the UV coordinates in the rendering engine, and then the synthesis calculation of the infrared image is carried out. Finally, the synthetic graph is used to detect the imaging spatial resolution R 1mn Perform resolution conversion to obtain an image with uniform resolution.

[0098] (2) Image synthesis. Based on GPU rendering, the center position of the chimney outlet in the M1 image H (h x ,h y ), the center of the bottom of the smoke plume of the M2 image (the default is (X2 / 2, 0)), and the above two points are used as the coincidence points of the two images. The M1 image is superimposed on the M2 image to obtain the initial overall infrared image.

[0099] For step 108, calculating the second distance from each pixel in the initial overall infrared image to the detector includes:

[0100] Calculate the UV coordinate of each pixel in the initial overall infrared image based on the UV coordinate of each pixel in the first infrared image and the UV coordinate of the center position of the smoke plume outlet in the second smoke plume image;

[0101] Based on the UV coordinate of each pixel in the initial overall infrared image, the number of pixels that each pixel in the second plume image deviates from the center of the plume outlet is calculated;

[0102] Based on the number of pixels that each pixel in the second plume image deviates from the center of the plume outlet, a second distance from each pixel in the initial overall infrared image to the detector is calculated.

[0103] In this step, the UV coordinates of each pixel in the overall infrared image are calculated based on the following formula:

[0104]

[0105] In the formula, (u 1m ,v 1n ) is the UV coordinate of the mnth pixel in the first infrared image; (u2, v2) is the UV coordinate of the center point of the smoke plume outlet in the second smoke plume image; (u 3m ,v 3n ) is the UV coordinate in the synthesized overall infrared image; (h x ,h y ) is the coordinate of the center position of the chimney outlet in the first infrared image; R 1mn is the resolution of the mnth pixel in the first infrared image; R 2mn is the resolution of the mnth pixel in the second plume image.

[0106] The number of pixels that each pixel in the second plume image deviates from the center of the plume outlet is calculated based on the following formula:

[0107]

[0108] The second distance from each pixel in the initial overall infrared image to the detector is calculated based on the following formula:

[0109]

[0110] in,

[0111]

[0112] In the formula, s mn LY is the number of pixels that the mnth pixel in the second plume image deviates from the center of the plume outlet; mnis the second distance from the mnth pixel in the initial overall infrared image to the detector; is the normal vector of the chimney outlet; Q is the detection distance from the detector to the chimney outlet; is the projection vector of the chimney outlet normal on the horizontal plane; is the unit vector of the detector’s viewing direction; and are respectively the projection vectors of the detection view direction in the X and Y directions in the XY plane of the rectangular coordinate system; They are The x and y components of Representation vector The length of , × represents the vector cross product.

[0113] Through the above calculation, the second distance from each pixel in the initial overall infrared image to the detector can be obtained.

[0114] Finally, step 110 includes:

[0115] For each pixel in the initial overall infrared image, perform:

[0116] Determine whether the first distance corresponding to the pixel is smaller than the second distance corresponding to the pixel;

[0117] If so, the grayscale value of the pixel is determined as the grayscale value of the pixel at the position corresponding to the pixel in the first infrared image;

[0118] If not, the grayscale value of the pixel is determined based on the following formula:

[0119]

[0120] Where min1 and max1 are the minimum and maximum values ​​of the radiant brightness of the grayscale quantization of the first infrared image, min2 and max2 are the minimum and maximum values ​​of the radiant brightness of the grayscale quantization of the second plume image, respectively. mn is the gray value of the pixel at the position corresponding to the pixel in the second plume image.

[0121] In this step, the occlusion relationship between pixels is determined by comparing the first distance and the second distance, and each pixel in the overall infrared image is assigned a value based on the occlusion relationship. Specifically, if the first distance corresponding to a certain pixel is smaller than the second distance, it means that the second plume image is occluded by the first infrared image at the location of the pixel, and therefore, the pixel in the first infrared image is used to assign a value to the overall infrared image. If the first distance corresponding to a certain pixel is larger than the second distance, it means that the first infrared image is occluded by the second plume image at the location of the pixel, and therefore, the pixel in the second plume image is used to assign a value to the overall infrared image. By analogy, each pixel in the overall infrared image is assigned a value to obtain the final overall infrared image.

[0122] The effectiveness of the method of the present application is demonstrated below with specific examples.

[0123] like Figure 4 and Figure 5 As shown in the figure, they are respectively a schematic diagram of the detection imaging of the target solid wall and a schematic diagram of the infrared radiation sequence image of the exhaust plume at multiple angles. By synthesizing the infrared images of the target solid wall and the plume images at different times and angles using the method of the present application, an overall infrared image sequence can be quickly and accurately generated, as shown in the figure. Figure 6 , Figure 7 and Figure 8 As shown. It can be seen that the present application has a good effect on dynamic target imaging.

[0124] like Figure 2 , Figure 3 As shown, an embodiment of the present invention provides a device for generating an overall infrared image of a moving target including an exhaust plume. The device embodiment can be implemented by software, or by hardware or a combination of software and hardware. From the hardware level, Figure 2 As shown, it is a hardware architecture diagram of a computing device where a device for generating an overall infrared image of a moving target including exhaust plumes provided by an embodiment of the present invention is located, except Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown in the figure, the computing device in which the device is located in the embodiment may also generally include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 3 As shown, as a device in a logical sense, the CPU of the computing device in which it is located reads the corresponding computer program in the non-volatile memory into the internal memory and runs it.

[0125] Please refer to Figure 3 The embodiment of the present invention provides a device for generating an overall infrared image of a moving target including an exhaust plume, the device comprising:

[0126] The first generating unit 300 is used to generate a first infrared image of the target solid wall at the current moment based on the detection information at the current moment and the pre-built target geometric grid model; the detection information includes the detection position, detection angle and detection resolution of the detector;

[0127] A first calculation unit 302, used to calculate a first distance from each pixel in the first infrared image to the detector;

[0128] A determination unit 304 is used to determine, based on the detection angle, a second smoke plume image consistent with the detection angle at the current moment from the predetermined multi-angle exhaust smoke plume infrared radiation sequence image;

[0129] The second generating unit 306 is used to synthesize the first infrared image and the second smoke plume image to generate an initial overall infrared image at a current moment;

[0130] A second calculation unit 308, used to calculate a second distance from each pixel in the initial overall infrared image to the detector;

[0131] The third generating unit 310 is used to assign a value to each pixel in the initial overall infrared image based on the relationship between each first distance and each second distance, so as to generate a final overall infrared image at the current moment.

[0132] In some implementations, the first generating unit 300 is configured to perform the following operations:

[0133] Perform polynomial fitting on the Planck formula of the object's own infrared radiation to obtain the first formula for calculating the radiation brightness of the object itself within a preset band;

[0134] Based on the current observation angle, the normal vector of each facet vertex in the grid model, and the temperature and emissivity of the target solid wall, the infrared radiation brightness value of each vertex is calculated using the first formula;

[0135] Based on the BRDF parameters of each face element in the mesh model, the reflected ambient infrared radiation brightness value of each face element vertex is calculated;

[0136] Based on the infrared radiation brightness value of each vertex and the infrared radiation brightness value of the reflected environment, a first infrared image of the target solid wall surface at the current moment is generated.

[0137] In some implementations, the first computing unit 302 is configured to perform the following operations:

[0138] For each pixel in the first infrared image, perform:

[0139] Determine the number of vertices contained in the pixel;

[0140] For each vertex contained in the pixel, the following operations are performed: based on the vector from the detector to the vertex and the vector from the detector to the target center, the difference between the distance from the vertex to the detector and the distance from the target center to the detector is calculated; in the GPU shader, the distance difference is written into the transparency channel of the vertex color to obtain the channel value of the vertex;

[0141] The average value of the channel value of each vertex is taken as the channel value of the pixel;

[0142] Based on the channel value of the pixel, a first distance from the pixel to the detector is calculated.

[0143] The calculation formula for the first distance is:

[0144] in,

[0145]

[0146] Where, L mn is the first distance from the mnth pixel in the first image to the detector; A mn is the channel value of the mnth pixel in the first image; A j and E j are the channel value of the jth vertex in the mnth pixel, the distance between the jth vertex and the detector, and the distance between the target center and the detector, j = 1, 2...K, K is the number of vertices contained in the mnth pixel; L is the length of the grid model; is the vector from the detector to the jth vertex; is the vector from the detector to the center of the target.

[0147] In some implementations, the second generating unit 306 is configured to perform the following operations:

[0148] The resolutions of the first infrared image and the second smoke plume image are uniformly converted based on the UV coordinates to obtain an image with uniform resolution;

[0149] For the images with unified resolution, the center position of the chimney outlet in the first infrared image and the center of the plume bottom in the second plume image are taken as the coincidence points of the two images. The first infrared image is superimposed on the second plume image to generate the initial overall infrared image at the current moment.

[0150] In some implementations, the second computing unit 308 is configured to perform the following operations:

[0151] Calculate the UV coordinate of each pixel in the initial overall infrared image based on the UV coordinate of each pixel in the first infrared image and the UV coordinate of the center position of the smoke plume outlet in the second smoke plume image;

[0152] Based on the UV coordinate of each pixel in the initial overall infrared image, the number of pixels that each pixel in the second plume image deviates from the center of the plume outlet is calculated;

[0153] Based on the number of pixels that each pixel in the second plume image deviates from the center of the plume outlet, a second distance from each pixel in the initial overall infrared image to the detector is calculated.

[0154] In some implementations, the third generating unit 310 is configured to perform the following operations:

[0155] For each pixel in the initial overall infrared image, perform:

[0156] Determine whether the first distance corresponding to the pixel is smaller than the second distance corresponding to the pixel;

[0157] If so, the grayscale value of the pixel is determined as the grayscale value of the pixel at the position corresponding to the pixel in the first infrared image;

[0158] If not, the grayscale value of the pixel is determined based on the following formula:

[0159]

[0160] Where min1 and max1 are the minimum and maximum values ​​of the radiant brightness of the grayscale quantization of the first infrared image, min2 and max2 are the minimum and maximum values ​​of the radiant brightness of the grayscale quantization of the second plume image, respectively. mn is the gray value of the pixel at the position corresponding to the pixel in the second plume image.

[0161] It should be noted that the overall infrared image generation device for a moving target including exhaust plumes provided in the above embodiment is only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the overall infrared image generation device for a moving target including exhaust plumes provided in the above embodiment and the overall infrared image generation method for a moving target including exhaust plumes belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0162] The embodiment of the present application also provides a computer device, please refer to Figure 3 The computer device includes a processor and a memory, in which at least one instruction, at least one program, a code set or an instruction set is stored, and the at least one instruction, at least one program, a code set or an instruction set is loaded and executed by the processor to implement the method for generating an overall infrared image of a moving target containing an exhaust plume provided in the above-mentioned method embodiments.

[0163] An embodiment of the present application also provides a computer-readable storage medium, on which is stored at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is loaded and executed by a processor to implement the method for generating an overall infrared image of a moving target including an exhaust plume provided in the above-mentioned method embodiments.

[0164] An embodiment of the present application also provides a computer program product, which includes a computer program. A processor of a computer device reads the computer program from a computer-readable storage medium, and the processor executes the computer program, so that the computer device executes the method for generating an overall infrared image of a moving target containing an exhaust plume as described in any of the above embodiments.

[0165] For the convenience of description, the above system or device is described by dividing it into various modules or units according to its functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0166] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0167] Finally, it should be noted that, in this article, relational terms such as first, second, third and fourth are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" 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, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0168] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for generating an overall infrared image of a moving target including an exhaust plume, characterized in that: The method comprises: Based on the detection information at the current moment and the pre-constructed target geometric grid model, a first infrared image of the target solid wall at the current moment is generated; the detection information includes the detection position, detection angle and detection resolution of the detector; Calculating a first distance from each pixel in the first infrared image to the detector; Based on the detection angle, determining a second smoke plume image consistent with the detection angle at the current moment from a predetermined multi-angle exhaust smoke plume infrared radiation sequence image; Synthesize the first infrared image and the second smoke plume image to generate an initial overall infrared image at the current moment; Calculating a second distance from each pixel in the initial overall infrared image to the detector; Based on the relationship between each of the first distances and each of the second distances, a value is assigned to each pixel in the initial overall infrared image to generate a final overall infrared image at the current moment.

2. The method according to claim 1, characterized in that The method of generating a first infrared image of the target solid wall at the current moment based on the detection information at the current moment and the pre-built target geometric grid model comprises: Perform polynomial fitting on the Planck formula of the object's own infrared radiation to obtain the first formula for calculating the radiation brightness of the object itself within a preset band; Based on the observation angle at the current moment, the normal vector of each facet vertex in the grid model, and the temperature and emissivity of the target solid wall, the first formula is used to calculate the infrared radiation brightness value of each vertex; Based on the BRDF parameters of each facet in the mesh model, the reflected ambient infrared radiation brightness value of each facet vertex is calculated; Based on the infrared radiation brightness value of each vertex and the infrared radiation brightness value of the reflected environment, a first infrared image of the target solid wall surface at the current moment is generated.

3. The method according to claim 2, characterized in that The calculating a first distance from each pixel in the first infrared image to the detector comprises: For each pixel in the first infrared image, the following steps are performed: Determine the number of vertices contained in the pixel; For each vertex contained in the pixel, the following operations are performed: based on the vector from the detector to the vertex and the vector from the detector to the target center, the difference between the distance from the vertex to the detector and the distance from the target center to the detector is calculated; in the GPU shader, the distance difference is written into the transparency channel of the vertex color to obtain the channel value of the vertex; The average value of the channel value of each vertex is taken as the channel value of the pixel; Based on the channel value of the pixel, a first distance from the pixel to the detector is calculated.

4. The method according to claim 3, characterized in that: The calculation formula of the first distance is: in, Where, L mn is the first distance from the mnth pixel in the first image to the detector; A mn is the channel value of the mnth pixel in the first image; A j and E j are the channel value of the jth vertex in the mnth pixel, the distance between the jth vertex and the detector, and the distance between the target center and the detector, j = 1, 2...K, K is the number of vertices contained in the mnth pixel; L is the length of the grid model; is the vector from the detector to the jth vertex; is the vector from the detector to the center of the target.

5. The method according to claim 2, characterized in that: The synthesizing the first infrared image and the second smoke plume image to generate an initial overall infrared image at the current moment includes: Uniformly converting the resolutions of the first infrared image and the second smoke plume image based on UV coordinates to obtain images with uniform resolutions; For the image with unified resolution, the center position of the chimney outlet in the first infrared image and the center of the bottom of the smoke plume in the second smoke plume image are taken as the overlapping points of the two images, and the first infrared image is superimposed on the second smoke plume image to generate the initial overall infrared image at the current moment.

6. The method according to claim 2, characterized in that Calculating a second distance from each pixel in the initial overall infrared image to the detector comprises: Calculate the UV coordinate of each pixel in the initial overall infrared image based on the UV coordinate of each pixel in the first infrared image and the UV coordinate of the center position of the smoke plume outlet in the second smoke plume image; Calculate the number of pixels of each pixel in the second smoke plume image that deviates from the center of the smoke plume outlet based on the UV coordinate of each pixel in the initial overall infrared image; Based on the number of pixels of each pixel in the second plume image that deviates from the center of the plume outlet, a second distance from each pixel in the initial overall infrared image to the detector is calculated.

7. The method according to claim 2, characterized in that The step of assigning a value to each pixel in the initial overall infrared image based on the relationship between each of the first distances and each of the second distances to generate a final overall infrared image at a current moment includes: For each pixel in the initial overall infrared image, the following steps are performed: Determine whether the first distance corresponding to the pixel is smaller than the second distance corresponding to the pixel; If yes, then determining the grayscale value of the pixel as the grayscale value of the pixel at the position corresponding to the pixel in the first infrared image; If not, the grayscale value of the pixel is determined based on the following formula: Where min1 and max1 are the minimum and maximum values ​​of the radiant brightness of the grayscale quantization of the first infrared image, min2 and max2 are the minimum and maximum values ​​of the radiant brightness of the grayscale quantization of the second plume image, respectively. mn is the gray value of the pixel at the position corresponding to the pixel in the second plume image.

8. A device for generating an overall infrared image of a moving target including an exhaust plume, characterized in that: The device comprises: A first generating unit is used to generate a first infrared image of the target solid wall at the current moment based on the detection information at the current moment and a pre-constructed target geometric grid model; the detection information includes a detection position, a detection angle and a detection resolution of the detector; A first calculation unit, used for calculating a first distance from each pixel in the first infrared image to the detector; A determination unit, configured to determine, based on the detection angle, a second smoke plume image consistent with the detection angle at a current moment from a predetermined multi-angle exhaust smoke plume infrared radiation sequence image; A second generating unit, configured to synthesize the first infrared image and the second smoke plume image to generate an initial overall infrared image at a current moment; A second calculation unit, used for calculating a second distance from each pixel in the initial overall infrared image to the detector; The third generating unit is used to assign a value to each pixel in the initial overall infrared image based on the relationship between each of the first distances and each of the second distances, so as to generate a final overall infrared image at a current moment.

9. A computer device, characterized in that: The computer device includes a memory and a processor, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory to implement the steps of any one of the methods described in claims 1-7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

Images