Invariance properties of polarization in active imagery and applications to contrast definition

Philippe Refregier; Francois Goudail

doi:10.1117/12.527071

19 November 2003 Invariance properties of polarization in active imagery and applications to contrast definition

Proceedings Volume 4829, 19th Congress of the International Commission for Optics: Optics for the Quality of Life; (2003) https://doi.org/10.1117/12.527071
Event: 19th Congress of the International Commission for Optics: Optics for the Quality of Life, 2002, Florence, Italy

Abstract

We recently proposed a rigorous definition of the minimal set of parameters which characterize the difference between two coherent and partially polarized states and we demonstrated that the optimal processing performance for signal processing tasks such as detection, localization or segmentation of spatial or temporal polarization variations is uniquely determined by these contrast parameters, which is a desirable quality for a rigorous contrast measure. This is a considerable simplification of the description of the physical situation since two states of partially polarized light are a priori defined by eight parameters, for example by their two Stokes vectors or by their two coherency matrices. The two contrast parameters are scalar functions of these eight parameters and are the statistical invariant parameters of two partially polarized states of coherent light. This definition of polarimetric contrast parameters simplifies the analysis and the specification of processing techniques for coherent polarimetric signals and images. We propose in this presentation to summarize and to illustrate these results.

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Philippe Refregier and Francois Goudail "Invariance properties of polarization in active imagery and applications to contrast definition", Proc. SPIE 4829, 19th Congress of the International Commission for Optics: Optics for the Quality of Life, (19 November 2003); https://doi.org/10.1117/12.527071

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KEYWORDS

Polarization

Signal processing

Polarimetry

Image processing

Image segmentation

Matrices

Statistical analysis

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