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5 October 2006 Partial polarization characterization based on the Kullback relative entropy
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The analysis of polarization and of depolarizing capabilities of materials is a technique of growing interest in different domains of applications. This is also the case for defence and security for which the determination of material characteristics can be of great interest in remote sensing and control application. However, until now, the analysis of polarization properties has been essentially limited to second order statistical characteristics such as Stokes vectors and/or Mueller matrices. There nevertheless exist other physical properties that cannot be characterized by such second order statistical characteristics. We demonstrate that the Kullback relative entropy leads to a relevant characterization of different properties that cannot be obtained by the measurements of Stokes vectors and/or Mueller matrices. For that purpose we show how the Kullback relative entropy, which is a physically meaningful measure of proximity between probability density functions (PDF), allows one to compare a partially polarized light with different optical states of reference. In particular, for optical waves with Gaussian fluctuations, the standard degree of polarization is a simple function of the Kullback relative entropy between the considered optical light and a totally depolarized light of the same intensity. It is demonstrated that one can generalize this relation between partially polarized light and different optical states of reference in order to measure new characteristics such as a degree of anisotropy, a degree of non gaussianity and a new degree degree of non-circularity. We discuss experimental configurations that can be discriminated with these new degrees of partially polarized light.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Philippe Réfrégier and François Goudail "Partial polarization characterization based on the Kullback relative entropy", Proc. SPIE 6394, Unmanned/Unattended Sensors and Sensor Networks III, 63940V (5 October 2006);

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