Adapted processing of catadioptric images using polarization imaging

Authors:
Samia Ainouz-Zemouche;Olivier Morel;Saleh Mosaddegh;David Fofi
Affiliations:
Information processing, Computer Science and Systems Laboratory, LITIS, Rouen, France;Le2i Laboratory, UMR, CNRS, University of Burgundy, France;Le2i Laboratory, UMR, CNRS, University of Burgundy, France;Le2i Laboratory, UMR, CNRS, University of Burgundy, France
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 3
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Abstract

A non parametric method that defines a pixel neighborhood within catadioptric images is presented in this paper. It is based on an accurate modeling of the mirror shape by using polarization imaging. Unlike the most of current processing methods in the literature, this method is non-parametric and can deal with the deformation of catadioptric images. This paper demonstrates how an appropriate neighborhood can be derived from the polarization parameters by estimation of the degree of polarization and the angle of polarization which in return directly provide an adapted neighborhood of each pixel that can be used to perform image derivation, edge detection, interest point detection and namely image matching, all in the catadioptric image plane.