Polarizance-Reflection-Transformation Representation Space for Sensing and Distinguishing Pure Systems
Dekui Li, Bingyi Liu, Kai Guo, Irene Estévez, Ángel Lizana, Juan Campos, Zhongyi Guo · IEEE Sensors Journal · 2024
Polarization representation spaces constructed by multidimensional polarization observations find their valuable position in target identification and analysis. In this paper, a new visual polarization representation space, Polarizance-Reflection-Transformation (PRT) space, has been proposed. The proposed PRT space is inspired by the Mueller matrix (MM) and able to effectively characterize the reflectivity, transformation of Stokes elements, dichroism, retardation, as well as depolarization simultaneously. Regarding the interacted systems with light, the PRT space clearly represents the corresponding physical meanings, and possesses the reliable transform relation to the standard polarization representation spaces. Notably, being superior to existing polarization representation spaces, it is capable of distinguishing the target systems undistinguishable. Particularly, the results of the Mie scattering system and polarizers strongly support the fact that the proposed PRT space significantly outperforms other existing polarization representation spaces with the pure systems, which evidences its remarkable potentials in target identification and analysis with high accuracy.