Comparison of the estimation of the degree of polarization from four or two intensity images degraded by speckle noise

TL;DR

This paper introduces a new statistical method to estimate the degree of polarization from two intensity images in speckle-noise degraded polarimetric imagery, improving flexibility over existing methods.

Contribution

A novel correlated measurement-based estimator for the degree of polarization using only two images is proposed, extending beyond the uncorrelated assumption of previous methods.

Findings

The proposed method performs well with simulated speckle-degraded data.

It compares favorably to four-image and OSCI estimators.

The method offers a flexible alternative in correlated measurement scenarios.

Abstract

Active polarimetric imagery is a powerful tool for accessing the information present in a scene. Indeed, the polarimetric images obtained can reveal polarizing properties of the objects that are not avalaible using conventional imaging systems. However, when coherent light is used to illuminate the scene, the images are degraded by speckle noise. The polarization properties of a scene are characterized by the degree of polarization. In standard polarimetric imagery system, four intensity images are needed to estimate this degree . If we assume the uncorrelation of the measurements, this number can be decreased to two images using the Orthogonal State Contrast Image (OSCI). However, this approach appears too restrictive in some cases. We thus propose in this paper a new statistical parametric method to estimate the degree of polarization assuming correlated measurements with only two intensity images. The estimators obtained from four images, from the OSCI and from the proposed method, are compared using simulated polarimetric data degraded by speckle noise.