The depolarization performances of scattering systems based on the Indices of Polarimetric Purity (IPPs)

Dynamic polarization fusion network (DPFN) for imaging in different scattering systems

Deep learning has broad applications in imaging through scattering media. Polarization, as a distinctive characteristic of light, exhibits superior stability compared to light intensity within scattering media. Consequently, the de-scattering network trained using polarization is expected to achieve enhanced performance and generalization. For getting optimal outcomes in diverse scattering conditions, it makes sense to train expert networks tailored for each corresponding condition. Nonetheless, it is often unfeasible to acquire the corresponding data for every possible condition. And, due to the uniqueness of polarization, different polarization information representation methods have different sensitivity to different environments. As another of the most direct approaches, a generalist network can be trained with a range of polarization data from various scattering situations, however, it requires a larger network to capture the diversity of the data and a larger training set to prevent overfitting. Here, in order to achieve flexible adaptation to diverse environmental conditions and facilitate the selection of optimal polarization characteristics, we introduce a dynamic learning framework. This framework dynamically adjusts the weights assigned to different polarization components, thus effectively accommodating a wide range of scattering conditions. The proposed architecture incorporates a Gating Network (GTN) that efficiently integrates multiple polarization features and dynamically determines the suitable polarization information for various scenarios. Experimental result demonstrates that the network exhibits robust generalization capabilities across continuous scattering conditions.

Self-attention module in a multi-scale improved U-net (SAM-MIU-net) motivating high-performance polarization scattering imaging

Polarization imaging has outstanding advantages in the field of scattering imaging, which still encounters great challenges in heavy scattering media systems even though there are helps from deep learning technology. In this paper, we propose a self-attention module (SAM) in multi-scale improved U-net (SAM-MIU-net) for the polarization scattering imaging, which can extract a new combination of multidimensional information from targets effectively. The proposed SAM-MIU-net can focus on the stable feature carried by polarization characteristics of the target, so as to enhance the expression of the available features, and make it easier to extract polarization features which help to recover the detail of targets for the polarization scattering imaging. Meanwhile, the SAM's effectiveness has been verified in a series of experiments. Based on proposed SAM-MIU-net, we have investigated the generalization abilities for the targets' structures and materials, and the imaging distances between the targets and the ground glass. Experimental results demonstrate that our proposed SAM-MIU-net can achieve high-precision reconstruction of target information under incoherent light conditions for the polarization scattering imaging.

Impact of color on polarization-based 3D imaging and countermeasures

Diffuse polarization-based 3D imaging has flourished with the ability to obtain the 3D shapes of objects without multiple detectors, active mode lighting, or complex mechanical structures, which are major drawbacks of other methods for 3D imaging in natural scenes. However, traditional polarization-based 3D imaging technology introduces color distortion when reconstructing the surface of multi-colored targets. We propose a polarization-based 3D imaging model to recover the 3D geometry of multi-colored Lambertian objects. In particular, chromaticity-based color removal theory is used to restore the intrinsic intensity, which is modulated only by the target shape, and we apply the recovered intrinsic intensity to address the orientation uncertainty of target normals due to azimuth ambiguity. Finally, we integrate the corrected normals to reconstruct high-precision 3D shapes. Experimental results demonstrate that the proposed model has the ability to reconstruct multi-colored Lambertian objects exhibiting non-uniform reflectance from single views under natural light conditions.

High-performance scanning-mode polarization based computational ghost imaging (SPCGI)

Computational ghost imaging (CGI) uses preset patterns and single-pixel detection, breaking through the traditional form of point-to-point imaging. In this paper, based on the Monte Carlo model, a reflective polarization based CGI (PCGI) system has been proposed and constructed under the foggy environments. And the imaging performances of the PCGI at different optical distances have been investigated and analyzed quantitatively. When the targets and the background have a small difference in reflectivity, the difference of polarization characteristics between the targets and the background can help the CGI to remove the interference of scattering light and improve the imaging contrast. Besides, in order to further improve imaging efficiency, a scanning-mode polarization based CGI (SPCGI) has also been proposed, in which the combination of polarization characteristics and the scanning-mode plays an important role to improve the CGI's imaging efficiency and imaging quality.

Unraveling the physical information of depolarizers

The link between depolarization measures and physical nature and structure of material media inducing depolarization is nowadays an open question. This article shows how the joint use of two complementary sets of depolarizing metrics, namely the Indices of polarimetric purity and the Components of purity, are sufficient to completely describe the integral depolarizing properties of a sample. Based on a collection of illustrative and representative polarimetric configurations, a clear and meaningful physical interpretation of such metrics is provided, thus extending the current tools and comprehension for the study and analysis of the depolarizing properties of material media. This study could be of interest to those users dealing with depolarization or depolarizing samples.

Near-infrared monocular 3D computational polarization imaging of surfaces exhibiting nonuniform reflectance

This paper presents a near-infrared (NIR) monocular 3D computational polarization imaging method to directly reconstruct the shape of surfaces exhibiting nonuniform reflectance. A reference gradient field is introduced to the weight constraints for globally correcting the ambiguity of the surface normal for a target with nonuniform reflectance. We experimentally demonstrated that our method can reconstruct the shape of surfaces exhibiting nonuniform reflectance in not only the near field but also the far field. Moreover, with the proposed method, the axial resolution can be kept constant even under different object distances as long as the ratio of the focal length to the object distance is fixed. The simplicity and robustness of the proposed method make it an attractive tool for the fast modeling of 3D scenes.

Measuring glucose concentration in a solution based on the indices of polarimetric purity

Polarization imaging is a powerful tool, which can be applied in biomedical diagnosis and many research fields. Here, we propose a new application of the indices of polarimetric purity (IPPs) composed of P1, P2, P3, to describe the glucose concentrations (GC) changes in the scattering system. The results suggest that P1 of the IPPs is a better indicator to GC in the solution than the degree of polarization (DoP) for the forward scattering detection. Meanwhile, the fitting relation among radius of scattering particle, GCs and P1 parameter has also been calculated, in which the error of inversion is no more than 4.73%. In the backscattering detection, the fitted frequency statistical histogram of the IPPs is used to measure the GCs, and their modes can represent changing trend of GCs.

Depolarization Characteristics of Different Reflective Interfaces Indicated by Indices of Polarimetric Purity (IPPs)

Compared with the standard depolarization index, indices of polarimetric purity (IPPs) have better performances to describe depolarization characteristics of targets with different roughnesses of interfaces under different incident angles, which allow us a further analysis of the depolarizing properties of samples. Here, we use IPPs obtained from different reflective interfaces as a criterion of depolarization property to characterize and classify targets covered by organic paint layers with different roughness. We select point-light source as radiation source with wavelength as 632.8 nm, and four samples, including Cu, Au, Al and Al₂O₃, covered by an organic paint layer with refractive index of n = 1.46 and Gaussian roughness of α = 0.05~0.25. Under different incident angles, the values of P₁, P₂, P₃ at divided 90 × 360 grid points and their mean values in upper hemisphere have been obtained and discussed in the IPPs space. The results show that the depolarization performances of the different reflective interfaces (materials, incident angles and surface roughness) are unique in IPPs space, providing us with a new avenue to analyze and characterize different targets.

Performances of Polarization-Retrieve Imaging in Stratified Dispersion Media

We constructed an active imaging model within 10 km of the atmosphere from the satellite to the ground based on Monte Carlo (MC) algorithm, and, because of the inhomogeneous distributions of the scattering particles in atmosphere environment, 10 km atmosphere layer was divided into ten layers in our model. The MC algorithm was used to simulate the transmission process of photons through the atmosphere. By launching lasers of linear polarization states from satellites to ground, the intensity, degree of polarization (DoP), polarization difference (PD), and polarization retrieve (PR) images can be obtained. The contrast of the image, peak signal to noise ratio (PSNR), and structural similarity index (SSI) were used to evaluate the imaging quality. The simulated results demonstrate that the contrast of images is degraded as the atmosphere becomes worse. However, PR imaging have a better contrast and better visibility in different atmospheric conditions. Meanwhile, we found that Mueller matrix (MM) can retrieve the original images very well in a certain range of atmospheric conditions. Finally, the simulation also shows that different wavelengths of light sources have different penetration characteristics, and, in general, infrared light shows better performances than visible light for imaging.

Sources of Asymmetry and the Concept of Nonregularity of n-Dimensional Density Matrices

The information contained in an n-dimensional (nD) density matrix ρ is parametrized and interpreted in terms of its asymmetry properties through the introduction of a family of components of purity that are invariant with respect to arbitrary rotations of the nD Cartesian reference frame and that are composed of two categories of meaningful parameters of different physical nature: the indices of population asymmetry and the intrinsic coherences. It is found that the components of purity coincide, up to respective simple coefficients, with the intrinsic Stokes parameters, which are also introduced in this work, and that determine two complementary sources of purity, namely the population asymmetry and the correlation asymmetry, whose weighted square average equals the overall degree of purity of ρ. A discriminating decomposition of ρ as a convex sum of three density matrices, viz. the pure, the fully random (maximally mixed) and the discriminating component, is introduced, which allows for the definition of the degree of nonregularity of ρ as the distance from ρ to a density matrix of a system composed of a pure component and a set of 2D, 3D,… and nD maximally mixed components. The chiral properties of a state ρ are analyzed and characterized from its intimate link to the degree of correlation asymmetry. The results presented constitute a generalization to nD systems of those established and exploited for polarization density matrices in a series of previous works.