Distributed target infrared polarization detection device and method

Abstract

This application discloses a distributed target infrared polarization detection device and method, relating to the field of infrared polarization light measurement. The device includes a distributed infrared polarization detection system and a data processing system. The distributed infrared polarization detection system includes multiple sliding tracks and multiple infrared polarization cameras, each of which is mounted on an infrared polarization camera. The infrared polarization cameras are used to simultaneously capture infrared polarization images of a target sample at different angles. The infrared polarization cameras change their orientation angle and detection angle via the sliding tracks. The data processing system is used to determine the polarization degree of the target sample based on the infrared polarization images at different angles. This application can improve measurement accuracy and efficiency.

Description

Technical Field

[0001] The present application relates to the field of infrared polarization measurement, and in particular to a distributed target infrared polarization detection device and method. Background Art

[0002] The target-background contrast of traditional photoelectric detection methods is not high enough, making it difficult to identify the target when detecting and imaging the target in complex environments, and it is impossible to distinguish the target from the complex background. In complex environments with interference such as grass and sand, the detection and identification capabilities of traditional photoelectric imaging for low-detectable targets such as stealth and camouflage are reduced. The polarization characteristics of a target generally change with the target's own physical and chemical characteristics and the observation angle. Once the target is determined, the physical and chemical characteristics of the target are also determined. At this time, the polarization characteristics of the target often depend on the observation angle. Most current measurement devices measure the polarization characteristics of an object in a single direction, or perform multi-angle time-sharing measurements. When measuring the relationship between the polarization characteristics of an object and the observation angle, these devices need to measure the polarization characteristics at different observation angles multiple times, and the angle needs to be manually adjusted during measurement. This makes the measurement process time-consuming and the measurement accuracy cannot be guaranteed. Summary of the Invention

[0003] The purpose of this application is to provide a distributed target infrared polarization detection device and method, which can improve measurement accuracy and efficiency.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a distributed target infrared polarization detection device, comprising:

[0006] Distributed infrared polarization detection system and data processing system;

[0007] The distributed infrared polarization detection system includes multiple sliding tracks and multiple infrared polarization cameras; the infrared polarization camera is set on each sliding track; the infrared polarization camera is used to simultaneously collect infrared polarization images of the target sample at different angles; the infrared polarization camera changes the direction angle and detection angle through the sliding tracks; the data processing system is used to determine the polarization degree of the target sample based on the infrared polarization images at different angles.

[0008] In one embodiment, the sliding track is an arc track; the arc track is set according to a set angle; and the target sample is set at the center of the arc track.

[0009] In one embodiment, the number of the arc-shaped tracks is three; and the set angle between every two of the arc-shaped tracks is 120°.

[0010] In one embodiment, the number of the infrared polarization cameras is three.

[0011] In one embodiment, the distributed target infrared polarization detection device further includes a sample stage; the target sample is arranged on the sample stage.

[0012] In one embodiment, the data processing system includes a controller and a plurality of computers;

[0013] Each computer is connected to an infrared polarization camera respectively; and the controller is connected to the computer.

[0014] In a second aspect, the present application provides a distributed target infrared polarization detection method, which is applied to the distributed target infrared polarization detection device, and the distributed target infrared polarization detection method includes:

[0015] Acquire infrared polarization images of target samples at different angles;

[0016] According to the infrared polarization images of the target sample at different angles, the image is enhanced using Gaussian pyramid and Laplacian pyramid to obtain image enhancement data;

[0017] The reflected light component is modeled according to the image enhancement data to obtain the infrared polarization degree of the target sample.

[0018] In one embodiment, obtaining infrared polarization images of a target sample at different angles specifically includes:

[0019] Adjust the position of the sliding track to obtain infrared polarization images at different azimuth angles collected by each infrared polarization camera with a detection angle of 0°;

[0020] The position of the sliding track was adjusted at intervals of 10° to obtain infrared polarization images of different azimuth angles collected by each infrared polarization camera at different detection angles.

[0021] In one embodiment, image enhancement is performed using Gaussian pyramid and Laplacian pyramid based on infrared polarization images of target samples at different angles to obtain image enhancement data, specifically including:

[0022] downsampling and interpolation dilation prediction are performed using a Gaussian pyramid according to the infrared polarization images of the target sample at different angles to obtain a Gaussian pyramid image;

[0023] Determine image data at various scales using a Laplacian pyramid according to the Gaussian pyramid image;

[0024] Reconstruct the image data at each scale to obtain image enhancement data.

[0025] In one embodiment, modeling the reflected light component according to the image enhancement data to obtain the infrared polarization degree of the target sample specifically includes:

[0026] Polarized BRDF modeling is performed based on image enhancement data to obtain specular reflection component, diffuse reflection component and volume scattering component;

[0027] Determining the linear polarization degree of infrared radiation from the target surface at multiple azimuth angles using the specular reflection component, diffuse reflection component, and volume scattering component;

[0028] The infrared polarization degree of the target sample is obtained by fitting the linear polarization degree of the infrared radiation of the target surface at multiple azimuth angles.

[0029] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0030] The present application provides a distributed target infrared polarization detection device and method. The distributed infrared polarization detection system includes multiple sliding tracks and multiple infrared polarization cameras; the infrared polarization camera is set on each sliding track; the infrared polarization camera is used to simultaneously collect infrared polarization images of the target sample at different angles; the infrared polarization camera changes the direction angle and detection angle through the sliding track; and the data processing system is used to determine the polarization degree of the target sample based on the infrared polarization images at different angles. By providing multiple sliding tracks and arranging infrared polarization cameras on the sliding tracks, infrared polarization images of the target sample at different angles can be directly collected simultaneously, thereby improving measurement efficiency. The infrared polarization camera changes the direction angle and detection angle through the sliding track to obtain infrared polarization images at different angles to determine the polarization degree of the target sample, overcoming the problem of unguaranteed measurement accuracy caused by a single angle or manual angle adjustment, thereby improving measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 Schematic diagram of the distributed target infrared polarization detection device.

[0033] Figure 2 Schematic diagram of the distributed target infrared polarization detection method.

[0034] Figure 3 A schematic diagram of image enhancement data is obtained by using Gaussian pyramid and Laplacian pyramid to perform image enhancement based on infrared polarization images of target samples at different angles.

[0035] Reference numerals: infrared polarization camera-1, sample stage-2, sliding track-3, computer-4. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0037] Distributed polarization detection is a method that utilizes distributed sensor networks and polarization sensing technology to achieve collaborative target detection and information acquisition. The goal of distributed polarization detection is to simultaneously detect a target from multiple perspectives using multiple distributed sensor nodes located in different spatial locations. This technology collects optical images of the target from different perspectives, enabling high-precision acquisition of polarization distribution information over a large area. Distributed imaging detection systems can extract target information across scenarios, platforms, and multiple perspectives at multiple granularities, including target image information (texture, shape, grayscale, etc.), target motion information, and target position information.

[0038] Therefore, by collecting distributed, multi-spectral polarization features of ground targets, we can establish a targeted polarization feature database for specific targets. By comparing the polarization feature differences between the measured target and the surrounding common background at various viewing angles and spectral bands, we can use the polarization features to identify and detect ground targets in low-light and complex environments.

[0039] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0040] In an exemplary embodiment, Figure 1 As shown, a distributed target infrared polarization detection device is provided, including: a distributed infrared polarization detection system and a data processing system.

[0041] The distributed infrared polarization detection system includes multiple sliding tracks 3 and multiple infrared polarization cameras 1; the infrared polarization camera 1 is set on each sliding track 3; the infrared polarization camera 1 is used to simultaneously collect infrared polarization images of the target sample at different angles; the infrared polarization camera 1 changes the direction angle and detection angle through the sliding track 3; the data processing system is used to determine the polarization degree of the target sample based on the infrared polarization images at different angles.

[0042] In an exemplary embodiment, the sliding track 3 is an arc track; the arc track is set according to a set angle; and the target sample is set at the center of the arc track.

[0043] In an exemplary embodiment, the number of the arc-shaped tracks is three; and the set angle between every two of the arc-shaped tracks is 120°.

[0044] In an exemplary embodiment, the number of the infrared polarization cameras is three, namely a first infrared polarization camera, a second infrared polarization camera, and a third infrared polarization camera, which are respectively installed on three arc tracks.

[0045] In an exemplary embodiment, the distributed target infrared polarization detection device further includes a sample stage 2 ; the target sample is arranged on the sample stage 2 .

[0046] In an exemplary embodiment, the data processing system includes a controller and multiple computers 4; each computer 4 is connected to an infrared polarization camera 1; and the controller is connected to the computers 4. In actual applications, each computer 4 is connected to a synchronizer, and the data processing system further includes a computer 4 connected to the controller to perform image processing and data fitting on the infrared polarization images captured by the multiple cameras.

[0047] In order to address the problem that when the target and the environment are integrated in complex environments such as low light intensity, dark environment, thick fog and smoke, coated nets, etc., the appearance, posture, and observation azimuth of different targets in the cluttered background show huge differences in camouflaged target characteristics, and a single angle is difficult to detect and identify, the distributed target infrared polarization detection device provided in this application can realize the detection and identification of optoelectronic low-detectable targets in complex environments.

[0048] In practical applications, the specific usage scenarios of the distributed target infrared polarization detection device are as follows.

[0049] The target sample is placed on the sample stage 2, which is located at the center of the distributed infrared polarization detection system. Sliding tracks 3 are arranged on the hemispherical device at 120° intervals, and the sliding tracks 3 are marked with angles. The multiple infrared polarization cameras 1 installed in the distributed infrared polarization detection system include a first infrared polarization camera, a second infrared polarization camera, and a third infrared polarization camera. The first infrared polarization camera is fixed to the sliding track 3 at an azimuth angle of 0°, the second infrared polarization camera is fixed to the sliding track 3 at an azimuth angle of 120°, and the third infrared polarization camera is fixed to the sliding track 3 at an azimuth angle of 120°. The first infrared polarization camera is connected to a first computer, the second infrared polarization camera is connected to a second computer, and the third infrared polarization camera is connected to a third computer.

[0050] The multiple computers 4 include a first computer, a second computer, a third computer, and a fourth computer. The first computer, the second computer, the third computer, and the fourth computer are connected through a controller. The first computer controls the first infrared polarization camera to acquire and save images, the second computer controls the second infrared polarization camera to acquire and save images, the third computer controls the third infrared polarization camera to acquire and save images, and the fourth computer synchronously controls the first computer, the second computer, and the third computer to acquire images, and performs image and data processing on the acquired images.

[0051] By providing multiple sliding rails 3 and arranging an infrared polarization camera 1 on the sliding rails 3, infrared polarization images of the target sample at different angles can be directly collected simultaneously, thereby improving measurement efficiency. The infrared polarization camera 1 changes the direction angle and detection angle through the sliding rails 3, and the polarization degree of the target sample is determined by infrared polarization images at different angles, thereby overcoming the problem of unguaranteed measurement accuracy caused by a single angle or manual angle adjustment, thereby improving measurement accuracy.

[0052] Based on the same inventive concept, embodiments of the present application also provide a distributed target infrared polarization detection method for implementing the aforementioned distributed target infrared polarization detection device. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations in one or more of the following embodiments of the distributed target infrared polarization detection method can be found in the aforementioned limitations on the distributed target infrared polarization detection device and will not be further elaborated here.

[0053] In an exemplary embodiment, a distributed target infrared polarization detection method is provided, which is applied to a distributed target infrared polarization detection device. The distributed target infrared polarization detection method includes:

[0054] Acquire infrared polarization images of the target sample at different angles.

[0055] According to the infrared polarization images of the target sample at different angles, Gaussian pyramid and Laplacian pyramid are used to perform image enhancement to obtain image enhancement data.

[0056] The reflected light component is modeled according to the image enhancement data to obtain the infrared polarization degree of the target sample.

[0057] In an exemplary embodiment, infrared polarization images of a target sample at different angles are obtained, specifically including: adjusting the position of a sliding track to obtain infrared polarization images of different azimuth angles captured by each infrared polarization camera with a detection angle of 0°; adjusting the position of the sliding track at intervals of 10° to obtain infrared polarization images of different azimuth angles captured by each infrared polarization camera at different detection angles.

[0058] In an exemplary embodiment, image enhancement is performed using a Gaussian pyramid and a Laplacian pyramid based on infrared polarization images of a target sample at different angles to obtain image enhancement data. The method specifically includes: downsampling and interpolation dilation prediction using a Gaussian pyramid based on the infrared polarization images of the target sample at different angles to obtain a Gaussian pyramid image; determining image data at various scales based on the Gaussian pyramid image using a Laplacian pyramid; and reconstructing the image data at various scales to obtain image enhancement data.

[0059] In an exemplary embodiment, the reflected light component is modeled according to the image enhancement data to obtain the infrared polarization degree of the target sample, specifically including: performing polarization BRDF modeling according to the image enhancement data to obtain a specular reflection component, a diffuse reflection component and a volume scattering component; using the specular reflection component, the diffuse reflection component and the volume scattering component to determine the linear polarization degree of infrared radiation of the target surface at multiple azimuth angles; fitting the linear polarization degree of infrared radiation of the target surface at multiple azimuth angles to obtain the infrared polarization degree of the target sample.

[0060] In an exemplary embodiment, Figure 2 and Figure 3 As shown, the specific process of the distributed target infrared polarization detection method in practical application is also provided, including the following steps.

[0061] (1) Sunlight is used as the light source of the entire system. Infrared polarization cameras are fixed on three sliding rails. The first infrared polarization camera, the second infrared polarization camera, and the third infrared polarization camera are located on the sliding rails at 0°, 120°, and 240° of the target azimuth to perform hemispherical spatial measurement on the target. The sample stage is placed in an outdoor test environment, such as a lawn. The sample stage and the infrared camera 1 to which the infrared polarization detection device belongs are on the same vertical axis.

[0062] (2) Adjust the position of the sliding track so that the detection angle of the three infrared polarization cameras is 0 degrees, and detect the target. The first infrared polarization camera collects the infrared polarization image of the target at an azimuth angle of 0°, the second infrared polarization camera collects the infrared polarization image of the target at an azimuth angle of 60°, and the third infrared polarization camera collects the infrared polarization image of the target at an azimuth angle of 120° and saves it. The saved infrared polarization image is named "detection zenith angle-azimuth angle".

[0063] (3) The detection angle range is 0°-60°. The detection angles of the three infrared polarization cameras are changed, and detection is performed at intervals of 10° and the images are saved.

[0064] (4) Image acquisition of the target sample is performed at different times of the day. The first set of detections is performed at 8:00 a.m., and the solar incidence angle at this time is recorded. Steps (2) and (3) are repeated every hour until 17:00, when the last set of detections is performed. The naming rule for the measurement folder is "time-solar incidence angle-detection zenith angle-azimuth angle".

[0065] (5) The Laplacian pyramid algorithm is used to enhance the collected infrared polarization image. The Laplacian pyramid algorithm can highlight image details such as edges and textures through different levels of decomposition. The process includes constructing a Gaussian pyramid, constructing a Laplacian pyramid, and reconstructing the image. The specific process is as follows.

[0066] Gaussian pyramid construction includes downsampling process and interpolation expansion prediction process.

[0067] The infrared polarization image is converted to the frequency domain using the Fast Fourier Transform (FFT), and then multiplied point by point with the frequency domain representation of the separable Gaussian filter. The image is then converted back to the spatial domain using the Inverse Fast Fourier Transform (IFFT), accelerating the convolution process to complete the Gaussian blur. Downsampling is then performed on the row and column directions of the convolved image to obtain the previous layer image. G 1 The calculation process uses an optimization method based on FFT and separable filters, and the expression is:

[0068] .

[0069] in, is the first layer image of the Gaussian pyramid, Yes The weight value of the Gaussian model at , is the coordinate of the infrared polarization image pixel.

[0070] Gaussian pyramid image G 1-1 Convert to the frequency domain through FFT, multiply the frequency domain filter corresponding to the interpolation expansion prediction point by point, and then convert back to the spatial domain through IFFT to obtain the Gaussian pyramid image of the next layer. The calculation process is:

[0071] .

[0072] .

[0073] After the Gaussian pyramid is built, a certain number of layers are configured for the infrared polarization image to construct the Laplacian pyramid. Let LP1 be the first layer of the Laplacian pyramid. The calculation method is to use the first layer image of the Gaussian pyramid Subtract the image from the previous level , the calculation formula is:

[0074] .

[0075] in , L It refers to the first L Layer, N is the upper limit value related to the number of layers, used to limit L The value range of .

[0076] The original infrared polarization image is reconstructed using the image data of each layer reconstructed by the Gaussian pyramid and Laplacian pyramid. The calculation formula is:

[0077] .

[0078] in During the reconstruction process, the polarization information of pixels at the boundary can be compensated by combining the reflection and scattering model of infrared polarized light on the object surface. For example, based on the material and surface characteristics of the object and the incident angle of the infrared polarized light, the polarization degree and polarization direction at the boundary are corrected to restore accurate polarization information at the boundary.

[0079] (6) Data processing is performed on the infrared polarization image reconstructed by the pyramid image. The components of the reflected light are modeled based on the processed data, and the target infrared polarization BRDF data is calculated. The infrared polarization bidirectional reflectance distribution function (BRDF) data of the target at three azimuth angles is calculated to obtain the polarization degree data of the three angles. Finally, the polarization degree of the target at the three azimuth angles is fitted to the target polarization degree. The calculation process is as follows.

[0080] When modeling polarized BRDF, the specular reflection component is modeled as follows:

[0081] .

[0082] in,

[0083] .

[0084] in, is the specular reflection component, M ij sis the Mueller matrix element in the specular reflection direction; θ i and are the zenith angle and azimuth angle of the incident direction, respectively; θ r and are the zenith angle and azimuth angle of the reflection direction, respectively; is the wavelength; α is the angle between the microfacet normal and the macronormal of the rough surface; β is the angle between the incident light and the microfacet normal; σ is the surface roughness constant of the object; Represents angle The spherical projection of All are empirical parameters. is a parameter related to roughness, which is determined by express.

[0085] Polarized BRDF modeling is performed on the target material surface. The expression is as follows:

[0086] .

[0087] in, is the three-component intensity expression of the target material surface, 、 and They are specular reflection component, diffuse reflection component and volume scattering component respectively; is the specular reflection component; is the diffuse component, =1 is the volume scattering component. is the wavelength.

[0088] In the infrared imaging system, the incident light is natural light, and the expression is , is the Stokes expression for the incident light, is the background radiation intensity, the Stokes vector of the infrared radiation polarization of the target surface is the reflected radiation vector and spontaneous emission vector Indicates that the expression is.

[0089] .

[0090] is the solid angle in the reflection direction, is the target object's own emissivity, I obg is the target radiation intensity, is the total reflectivity distribution function, is the 0° linear polarization reflection efficiency distribution function, is the 45° linear polarization reflection efficiency distribution function, is the circular polarization reflection efficiency distribution function.

[0091] Mueller matrix M ij Elements in Substituting into the Stokes vector expression of infrared radiation polarization we get:

[0092] .

[0093] in, I is the total intensity of the reflected light; Q is the difference in linear polarization between the horizontal and vertical directions of the reflected light; U is the linear polarization difference of the reflected light in the ±45° direction; V is the circular polarization component of the reflected light, The expression is as follows, It represents the Fresnel reflectivity of the component of the light wave parallel to the incident surface, represents the Fresnel reflectivity of the component perpendicular to the incident surface, It is the angle between the reflection direction and the two planes formed by the surface normal of the object and the microfacet normal. and is the reflection coefficient of the target to the p and s components of the incident light.

[0094] .

[0095] When detecting at one azimuth angle, the linear polarization degree of infrared radiation on the target surface The expression is:

[0096] .

[0097] When modeling BRDF, the specular reflection component of the material surface is dominant. The specular reflection is mainly determined by the Fresnel reflection law, which describes the relationship between the incident angle and the reflectivity. The distributed polarization degree of the target material surface is defined based on the distribution of the specular reflection amount of the target received by the receiver from different angles. That is, when the distributed infrared detection system detects, the overall polarization degree of the target is measured by the proportion of the specular reflection at the three angles of 0°, 120° and 240° in the total specular reflection in the three directions. The distribution of the polarization degree in the system is measured, and the overall polarization degree of the target is The expression is as follows.

[0098] .

[0099] 、 、 The specular reflections at three angles of 0°, 120° and 240° are respectively, The polarization degrees at three angles: 0°, 120°, and 240°.

[0100] Set the reflection amount Substitute the Stokes vector What is obtained is the overall polarization degree expression of the target.

[0101] This application has the following technical effects:

[0102] The distributed collaborative detection camera assembly provided in this application can collect polarization images of the sample to be tested at different angles in the sample table. After computer processing, the polarization data of the sample to be tested at different angles can be obtained. Then, through fitting, the final target polarization data can be determined and used as the measurement result value of the sample to be tested. Distributed infrared polarization detection detects the target from multiple perspectives at the same time and collects polarization images at different angles. By comparing the polarization feature differences between the target and the background under different perspectives and spectral bands, that is, the polarization difference between the target and the background, it can effectively identify ground targets in low-light complex environments (such as low light intensity, darkness, thick fog and smoke, and scenes where the target and the environment are integrated through a coating network). It greatly enhances the detection and identification capabilities in complex environments, effectively solves the technical bottleneck of a single sensor that is difficult to balance high resolution and large field of view, and provides strong support for the subsequent wider and more accurate application of polarization characteristics in military reconnaissance, environmental monitoring, industrial testing and other fields, and improves the understanding and application capabilities of polarization information.

[0103] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0104] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0105] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0106] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0107] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0108] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A distributed target infrared polarization detection device, characterized in that: include: Distributed infrared polarization detection system and data processing system; The distributed infrared polarization detection system includes multiple sliding tracks and multiple infrared polarization cameras; the infrared polarization camera is set on each sliding track; the sliding track is an arc track; the arc track is set according to a set angle; the target sample is set at the center of the arc track; the number of the arc tracks is three; the set angle between every two arc tracks is 120°; the infrared polarization camera is used to simultaneously collect infrared polarization images of the target sample at different angles; the infrared polarization camera changes the direction angle and detection angle through the sliding track; the data processing system is used to determine the polarization degree of the target sample according to the infrared polarization images at different angles; specifically: according to the infrared polarization images of the target sample at different angles, Gaussian pyramid and Laplacian pyramid are used to perform image enhancement to obtain image enhancement data; polarization BRDF modeling is performed based on the image enhancement data to obtain specular reflection component, diffuse reflection component and volume scattering component; Determining the linear polarization degree of infrared radiation from the target surface at multiple azimuth angles using the specular reflection component, diffuse reflection component, and volume scattering component; The infrared polarization degree of the target sample is obtained by fitting the linear polarization degree of the infrared radiation of the target surface at multiple azimuth angles.

2. The distributed target infrared polarization detection device according to claim 1, characterized in that: The number of the infrared polarization cameras is three.

3. The distributed target infrared polarization detection device according to claim 1, characterized in that: The distributed target infrared polarization detection device further includes a sample stage; the target sample is arranged on the sample stage.

4. The distributed target infrared polarization detection device according to claim 1, characterized in that: The data processing system includes a controller and a plurality of computers; Each computer is connected to an infrared polarization camera respectively; and the controller is connected to the computer.

5. A distributed target infrared polarization detection method, characterized in that: The distributed target infrared polarization detection method is applied to the distributed target infrared polarization detection device according to any one of claims 1 to 4, and the distributed target infrared polarization detection method includes: Acquire infrared polarization images of target samples at different angles; According to the infrared polarization images of the target sample at different angles, the image is enhanced using Gaussian pyramid and Laplacian pyramid to obtain image enhancement data; The reflected light component is modeled according to the image enhancement data to obtain the infrared polarization degree of the target sample, specifically including: performing polarization BRDF modeling according to the image enhancement data to obtain a specular reflection component, a diffuse reflection component and a volume scattering component; using the specular reflection component, the diffuse reflection component and the volume scattering component to determine the linear polarization degree of infrared radiation of the target surface at multiple azimuth angles; and fitting the linear polarization degree of infrared radiation of the target surface at multiple azimuth angles to obtain the infrared polarization degree of the target sample.

6. The distributed target infrared polarization detection method according to claim 5, characterized in that: Obtain infrared polarization images of the target sample at different angles, including: Adjust the position of the sliding track to obtain infrared polarization images at different azimuth angles collected by each infrared polarization camera with a detection angle of 0°; The position of the sliding track was adjusted at intervals of 10° to obtain infrared polarization images of different azimuth angles collected by each infrared polarization camera at different detection angles.

7. The distributed target infrared polarization detection method according to claim 5, characterized in that: According to the infrared polarization images of the target sample at different angles, the Gaussian pyramid and Laplacian pyramid are used to perform image enhancement to obtain image enhancement data, including: downsampling and interpolation dilation prediction are performed using a Gaussian pyramid according to the infrared polarization images of the target sample at different angles to obtain a Gaussian pyramid image; Determine image data at various scales using a Laplacian pyramid according to the Gaussian pyramid image; Reconstruct the image data at each scale to obtain image enhancement data.

Images