A Scattering Environment Imaging Characterization Method Based on Polarization Purity

Abstract

This invention discloses a method for imaging and characterizing a scattering environment based on polarization purity parameters. Step 1: Construct a polarization Mueller imaging system for a scattering water environment, modulate the polarization generator and polarization analyzer in the imaging system, and calculate the Mueller matrix corresponding to the target scene under the scattering environment. Step 2: Calculate the images corresponding to the three polarization purity indices, and characterize the target scene under the scattering environment based on these three images. Step 3: Differentiate target objects of different materials. Step 4: Enhance the images corresponding to the three polarization purity indices to further improve image detail recognition and image contrast, obtaining high-quality imaging images far exceeding those based on light intensity map technology. Compared with existing technologies, this invention has a more complete depolarization characterization capability for target objects, significantly enhances image contrast and enriches image details under strong scattering environments, and highlights target objects of different materials in the target scene.

Description

Technical Field

[0001] This invention relates to the fields of polarization imaging in scattering medium imaging and polarization imaging detection technology, and particularly to a polarization image-based enhancement method in a scattering environment. Background Technology

[0002] Polarization, as an inherent characteristic of electromagnetic waves, has been proven to be a key technology for target characterization, attracting widespread research and attention in various fields such as ocean and atmospheric remote sensing. Polarization techniques (such as polarization lidar, polarization remote sensing, and polarization imaging) can obtain not only the intensity information of objects but also their polarization information, such as degree of polarization, polarization angle, and depolarization index, greatly improving the detection and reconstruction capabilities of target information under complex conditions. Among various polarization characteristic measures, the Mueller matrix is ​​the most promising. It contains independent parameters and is considered the "optical fingerprint" of the material of interest. Because the Mueller matrix is ​​related to various physical properties such as target material, observation direction, incident angle, and object shape, it has been widely applied through polarization measurement and imaging configuration.

[0003] In marine optics, the demand for detecting underwater targets is increasing; however, one of the biggest challenges is that the scattering and absorption of light by underwater / oceanic particles leads to a significant deterioration in image quality. In turbid scattering water environments, the primary factor causing image quality degradation is the interference of backscattered light, which is partially polarized and its polarization characteristics differ from those of the target signal light. Therefore, acquiring and processing polarization information can effectively suppress the influence of backscattered light, ultimately achieving a significant improvement in image quality. Although existing techniques for separating target object light from background scattered light by estimating the intensity of scattered light using the Mueller matrix have been published, the relevant physical properties are not clearly reflected in the measured Mueller matrix. Therefore, how to more comprehensively characterize the target object in the Mueller matrix is ​​a pressing technical problem to be solved in this field. Depolarization methods have been proven to effectively identify targets in scattering media. Depolarization is the most important metric related to the physical / polarization properties of the scattering medium. This method uses a single metric to characterize the depolarization effect of the object, and therefore may be limited when dealing with strong scattering conditions. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, this invention discloses a scattering environment imaging characterization method based on polarization purity parameters. Based on the measurement of the Mueller matrix corresponding to the scene in the scattering environment and the solution of the polarization purity parameters, the method utilizes the depolarization characteristics evaluation index of three different dimensions in polarization purity and uses the corresponding intensity map for scene characterization in the scattering environment.

[0005] This invention is achieved using the following technical solution:

[0006] A method for characterizing scattering environment based on polarization purity parameters, comprising the following steps:

[0007] Step 1: Build a polarization Mueller imaging system for a scattering water environment, modulate the polarization generator and polarization analyzer in the imaging system, and calculate the Mueller matrix M of the object corresponding to the target scene in the scattering environment.

[0008]

[0009] Among them, S 01 S 11 S 21 S 31 The Stokes vector corresponding to horizontally linearly polarized light, S 02 S 12 S 22 S 32 For vertically linearly polarized light, the corresponding Stokes vector, S 03 S 13 S 23 S 33 The Stokes vector corresponding to linearly polarized light at 45°, S 04 S 14 S 24 S 34 The Stokes vector corresponding to right-handed circularly polarized light;

[0010] Step 2: Solve for the polarization purity based on the Mueller matrix to obtain the corresponding Hamiltonian matrix:

[0011]

[0012] Where, m ij This represents the element in the i-th row and j-th column of the Mueller matrix. The matrix σ represents the Kronecker ride, * represents the complex conjugate of the matrix, and σ represents the matrix multiplication. i ,σ j Let i and j represent the i-th or j-th Pauli matrix, respectively, where i, j = {0, 1, 2, 3}. The corresponding expressions for the Pauli matrices are as follows:

[0013]

[0014] The three indices P1, P2, and P3 for calculating polarization purity are expressed as follows:

[0015]

[0016]

[0017]

[0018] Where trH represents the trace of Hamiltonian matrix H, and λ0, λ1, λ2, and λ3 represent the four eigenvalues ​​of Hamiltonian matrix H.

[0019] Image representation of target scenes under scattering environment based on three indicators of polarization purity;

[0020] Step 3: Based on the differences in the three-dimensional spatial distribution of the three indicators, target objects of different materials in a scattering environment can be distinguished.

[0021] Step 4: Perform image enhancement on the three polarization purity index sub-images to improve image detail recognition and image contrast, obtaining high-quality imaging images that far exceed those based on light intensity map technology.

[0022] Compared with the prior art, the beneficial effects and advantages of the present invention are as follows:

[0023] 1. Compared with a single depolarization rate index, the polarization purity map has a more complete depolarization characterization capability for target objects, and can be used to distinguish and highlight target objects of different materials in the target scene.

[0024] 2. Since the image contrast corresponding to polarization purity is significantly higher than that of traditional light intensity image mode, by combining image enhancement algorithms to process the polarization purity map, the image contrast can be further improved, helping to overcome the limitations of visible distance and object discernibility in strong scattering media.

[0025] 3. Applying the intensity maps corresponding to the three polarization purity indices to scene characterization under scattering conditions provides a more complete depolarization characterization capability for target objects compared to a single depolarization rate index. Under strong scattering conditions, it can significantly enhance image contrast and enrich image details, highlighting target objects of different materials in the target scene. Attached Figure Description

[0026] Figure 1 This is an overall flowchart of a scattering environment imaging characterization method based on polarization purity parameters according to the present invention.

[0027] Figure 2 This is a schematic diagram of an example of a polarization Mueller imaging system in a scattering water environment used in this invention.

[0028] Figure 3 Examples of the original light intensity map and three polarization purity indices (P1, P2, P3) in turbid scattering water environment are shown, where: (3a) is the original light intensity map; (3b), (3c), and (3d) are the three polarization purity indices (P1, P2, P3) respectively.

[0029] Figure 4The following are comparison diagrams of the discrimination of three different regions: (4a) light intensity histogram, (4b) three-dimensional polarization purity distribution map;

[0030] Figure 5 The images show a comparison of the effects of image enhancement based on different images, where: (5a) is the original intensity image; (5b) is the enhanced original intensity image; and (5c), (5d), and (5e) are the polarization purity images enhanced by the CLAHE algorithm, respectively.

[0031] Figure label:

[0032] 1. Laser source, 2. Laser beam expander and collimator, 3. First polarizer, 4. First quarter-wave plate, 5. Water tank containing turbid scattering water, 6. Target object, 7. Second quarter-wave plate, 8. Second polarizer, 9. Light intensity detector (CCD). Detailed Implementation

[0033] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] like Figure 1 As shown, this invention provides a scattering environment imaging characterization method based on polarization purity parameters. The method includes the following steps:

[0035] Step 1: Build a polarization Mueller imaging system for scattering water environment, modulate the polarization generator (PSG) and polarization analyzer (PSA) in the imaging system, and calculate the Mueller matrix diagram corresponding to the target scene under scattering environment.

[0036] like Figure 2 The diagram shows an example of a polarization Mueller imaging system in a scattering water environment used in this invention. The light emitted from the laser source 1 passes through the laser beam expander and collimator 2, then through the first polarizer 3 and the first quarter-wave plate 4 to illuminate the underwater target object 6, which is placed in a water tank 5 containing turbid scattering water. After reflection from the underwater target object 6, the emitted light passes through the second polarizer 7 and the second quarter-wave plate 8 before entering the light intensity detection device CCD 9. Different polarization states of the incident light are obtained by adjusting the first polarizer 3 and the first quarter-wave plate 4, and different polarization states of the polarization analyzer (PSA) are obtained by adjusting the second polarizer 7 and the second quarter-wave plate 8. A Mueller matrix corresponding to an unknown scene is calculated. The 16 elements of the Mueller matrix are calculated using four different combinations of the output polarization states of the incident light, typically using the following four sets of polarization states of the incident light:

[0037] 1) Horizontally linearly polarized light, the corresponding Guan Stokes vector is (S 01 S 11 S 21 S31 ) T ;

[0038] 2) For vertically linearly polarized light, the corresponding Stokes vector is (S 02 S 12 S 22 S 32 ) T ;

[0039] 3) For 45° linearly polarized light, the corresponding Stokes vector is (S 03 S 13 S 23 S 33 ) T ;

[0040] 4) Right-handed circularly polarized light, the corresponding Stokes vector is (S 04 S 14 S 24 S 34 ) T .

[0041] By modulating the polarization generator (PSG) and polarization analyzer (PSA) in the imaging system respectively, the output polarization states of the incident light with the four different combinations mentioned above are obtained. The Mueller matrix of the object is then calculated, and the expression is as follows:

[0042]

[0043] Step 2: Solve for the polarization purity based on the Mueller matrix to obtain the corresponding Hamiltonian matrix:

[0044]

[0045] Where, m ij This represents the element in the i-th row and j-th column of the Mueller matrix. The matrix σ represents the Kronecker ride, * represents the complex conjugate of the matrix, and σ represents the matrix multiplication. i ,σ j Let i and j represent the i-th or j-th Pauli matrix, respectively, where i, j = {0, 1, 2, 3}. The corresponding expressions for the Pauli matrices are as follows:

[0046]

[0047] The indices P1, P2, and P3 for the three polarization purities are calculated using the following expressions:

[0048]

[0049]

[0050]

[0051] Where trH represents the trace of the Hamiltonian matrix H.

[0052] The polarization purity index must meet the following conditions:

[0053] 0≤P1≤P2≤P3≤1 (5)

[0054] The Hamiltonian matrix H is a positive semi-definite matrix with four eigenvalues, satisfying λ0≥λ1≥λ2≥λ3≥0.

[0055] like Figure 3 The image shows examples of the original light intensity map and three polarization purity indices (P1, P2, P3) in a turbid scattering water environment. (3a) is the original light intensity map; (3b), (3c), and (3d) are the three polarization purity indices (P1, P2, P3), respectively. The original light intensity image and the three polarization purity indices in a turbid underwater scene are presented. It can be seen that even without any image enhancement techniques, the polarization purity map still has significantly high image quality, revealing image details that are not visible in the original light intensity image.

[0056] The target scene under the scattering environment is represented by the image corresponding to the three indicators in the polarization purity parameter; the polarization purity sub-image is used to represent the target scene under the scattering environment to improve the representation quality (such as image contrast and detail discrimination).

[0057] Step 3: Based on the differences in the three-dimensional spatial distribution of the three indicators, target objects of different materials can be distinguished.

[0058] For example: Figure 3 The three regions within the matrix frame in the original light intensity image (corresponding to the metal coin, plastic coin, and plastic backing, respectively).

[0059] like Figure 4 The figure shows a comparison of the discrimination of three different regions. The distribution of pixels in each of the three regions is plotted in the figure. It can be seen that it is difficult to distinguish target objects of different materials from the light intensity distribution of the light intensity histogram in (4a), but they can be clearly distinguished from the three-dimensional polarization purity distribution map in (4b). This result indicates that using the depolarization characteristics evaluation index of three different dimensions of polarization purity, and comparing the intensity map corresponding to it with that of other indicators, for scene characterization under scattering environments can be used to distinguish and highlight different materials / objects in the target scene.

[0060] Step 4: Image enhancement is performed on the three polarization purity index sub-images to further improve image detail recognition and contrast, resulting in high-quality imaging images far exceeding those based on intensity map technology. This achieves image restoration effects far surpassing those of intensity map imaging techniques.

[0061] For the high-quality imaging images obtained through the above process, which far exceed those based on light intensity map technology, image enhancement can further improve the imaging quality: since the image contrast corresponding to polarization purity is significantly higher than that in traditional light intensity image modes, image contrast can be further improved by combining image enhancement algorithms (such as adaptive histogram equalization, CLAHE). Figure 5 The image shows a comparison of the effects of image enhancement based on different images, where (5a) is the original intensity image; (5b) is the enhanced original intensity image; and (5c), (5d), and (5e) are the polarization purity images enhanced by the CLAHE algorithm, respectively. The comparison of the effects of CLAHE enhancement on the original light intensity image and the three polarization purity index images at two different concentrations is shown. It can be seen that image enhancement based on the images corresponding to the three polarization purity indices can further improve the image detail recognition and image contrast, obtaining a high-quality imaging image, significantly better than the image enhancement effect based on light intensity images. This method breaks through the limitations of traditional light intensity-based imaging modes and overcomes the limitations of light intensity images in terms of visible distance and object discernibility.

[0062] This invention discloses a scattering environment imaging characterization method based on polarization purity parameters. Based on the measurement of the Mueller matrix corresponding to the scene in the scattering environment and the solution of the polarization purity parameters, the method uses the depolarization characteristics evaluation index of three different dimensions in polarization purity and uses the corresponding intensity map for scene characterization in the scattering environment.

[0063] The above description is merely a preferred embodiment for demonstrating the technical ideas and features of the present invention, and is intended to enable those skilled in the art to understand the invention and implement it accordingly. It is not intended to limit the present invention. Modifications, substitutions, equivalent changes, etc., made within the spirit and principles of the present invention should all be within the protection scope of the present invention.

Claims

1. A method for characterizing scattering environment based on polarization purity parameters, characterized in that, The method includes the following steps: Step 1: Build a polarization Mueller imaging system for a scattering water environment, modulate the polarization generator and polarization analyzer in the imaging system, and calculate the Mueller matrix M of the object corresponding to the target scene in the scattering environment. ; （1） in, This is the Stokes vector corresponding to horizontally linearly polarized light. The Stokes vector corresponding to vertically linearly polarized light. This represents the Stokes vector corresponding to linearly polarized light at 45°. This is the Stokes vector corresponding to right-handed circularly polarized light; Step 2: Solve for the polarization purity based on the Mueller matrix to obtain the corresponding Hamiltonian matrix: ; （2） in, This represents the element in the i-th row and j-th column of the Mueller matrix. The asterisk (*) indicates the Kronecker flight, and the asterisk (*) indicates the complex conjugate of the matrix. Let i and j represent the i-th or j-th Pauli matrix, respectively. The Pauli matrix is ​​expressed as follows: ; （3） Three indicators for calculating polarization purity and The expression is as follows: ;（4） Where trH represents the trace of Hamiltonian matrix H, and 𝜆0, 𝜆1, 𝜆2, 𝜆3 represent the four eigenvalues ​​of Hamiltonian matrix H; Image representation of target scenes under scattering environment based on three indicators of polarization purity; Step 3: Based on the differences in the three-dimensional spatial distribution of the three indicators, target objects of different materials in the scattering environment can be distinguished. The differences can be made based on the differences in the three-dimensional distribution space of the corresponding polarization purity diagram. Step 4: Perform image enhancement on the three polarization purity index sub-images to improve image detail recognition and image contrast.

Images