Performances of Polarization-Retrieve Imaging in Stratified Dispersion Media

Abstract

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.

High-Performance Polarization Imaging Reconstruction in Scattering System under Natural Light Conditions with an Improved U-Net

“…Due to the high reflectivity and low deflection characteristics of steel, the image obtained through the scattering medium retains a large amount of target information. It can also be seen that the polarization characteristics of steel and paper are quite different from Table 2 [19,56]. Therefore, the model-DoP can also identify the outline of the target.…”

“…Following developments in polarization transmission theory in recent years [17,18], polarization technology now plays an important role in solving target imaging from scattering media [19][20][21]. In recent years, physical models and image processing methods based on polarization information have been proposed to improve the clarity of imaging in scattering media [22,23].…”

“…Shao et al developed an active polarization imaging technology based on wavelength selection [31], which uses the dependence of scattering light at different wavelengths in a turbid underwater situation. In addition, Guo et al obtained the Muller matrix (MM) of a scattering medium based on the Monte Carlo (MC) algorithm [3] and proposed a polarization inversion method to study polarization transmission characteristics in layered dispersion systems [15,17,[32][33][34], a layered atmosphere [19], and underwater environments [5].…”

High-performance deep-learning based polarization computational ghost imaging with random patterns and orthonormalization

“…Fortunately, there always exists difference in polarization characteristics between the targets and the backgrounds. Moreover, polarized lights also have good anti-scattering effects [22][23][24][25]. Therefore, polarization computational ghost imaging provides additional information for contrast-enhanced target recognition in traditional ghost imaging [26][27][28][29].…”

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

“…When light interacts with targets, the polarization of the incident light may undergo a modification, carrying structural information of the targets. Therefore, it is important to characterize the process of the reflective polarization for exploring the polarization distributions and revealing the features of the surface, which can be used in polarization remote sensing [ 9 , 10 ], target detection and recognition [ 11 , 12 , 13 , 14 ], especially in the hidden-target identification. When the sample is not an ideal smooth surface, the reflected light will have different propagating directions, namely scattering.…”