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Proceedings Paper • Open Access

Statistically independent region models applied to correlation and segmentation techniques
Author(s): Philippe Refregier; Francois Goudail; Christophe Chesnaud

Paper Abstract

Recently new approaches for location and/or segmentation of objects with unknown gray levels embedded in non-overlapping noise have been proposed. These techniques are based on the Statistically Independent Region (SIR) model and are optimal in the maximum likelihood sense. In this paper, we review their theoretical bases and propose a unified approach which enlarges their field of application.

Paper Details

Date Published: 2 June 1999
PDF: 33 pages
Proc. SPIE 10296, 1999 Euro-American Workshop Optoelectronic Information Processing: A Critical Review, 102960C (2 June 1999); doi: 10.1117/12.365909
Show Author Affiliations
Philippe Refregier, Ecole Nationale Superieure de Physique de Marseille (France)
Francois Goudail, Ecole Nationale Superieure de Physique de Marseille (France)
Christophe Chesnaud, Ecole Nationale Superieure de Physique de Marseille (France)


Published in SPIE Proceedings Vol. 10296:
1999 Euro-American Workshop Optoelectronic Information Processing: A Critical Review
Philippe Refregier; Bahram Javidi, Editor(s)

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