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Performances of Polarization-Retrieve Imaging in Stratified Dispersion Media

Xinyang Wang, Tianwei Hu, Dekui Li, Kai Guo, Jun Gao, Zhongyi Guo

2020Remote Sensing35 citationsDOIOpen Access PDF

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.

Topics & Concepts

Polarization (electrochemistry)OpticsDegree of polarizationRemote sensingAtmosphere (unit)ScatteringPhysicsEnvironmental scienceMaterials scienceMeteorologyGeologyPhysical chemistryChemistryOptical Polarization and EllipsometryRemote Sensing in AgricultureAdvanced Image Fusion Techniques
Performances of Polarization-Retrieve Imaging in Stratified Dispersion Media | Litcius