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Proceedings Paper

Underwater color constancy: enhancement of automatic live fish recognition
Author(s): Majed Chambah; Dahbia Semani; Arnaud Renouf; Pierre Courtellemont; Alessandro Rizzi
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Paper Abstract

We present in this paper some advances in color restoration of underwater images, especially with regard to the strong and non uniform color cast which is typical of underwater images. The proposed color correction method is based on ACE model, an unsupervised color equalization algorithm. ACE is a perceptual approach inspired by some adaptation mechanisms of the human visual system, in particular lightness constancy and color constancy. A perceptual approach presents a lot of advantages: it is unsupervised, robust and has local filtering properties, that lead to more effective results. The restored images give better results when displayed or processed (fish segmentation and feature extraction). The presented preliminary results are satisfying and promising.

Paper Details

Date Published: 18 December 2003
PDF: 12 pages
Proc. SPIE 5293, Color Imaging IX: Processing, Hardcopy, and Applications, (18 December 2003); doi: 10.1117/12.524540
Show Author Affiliations
Majed Chambah, Univ. de La Rochelle (France)
Dahbia Semani, Univ. de La Rochelle (France)
Arnaud Renouf, Univ. de La Rochelle (France)
Pierre Courtellemont, Univ. de La Rochelle (France)
Alessandro Rizzi, Univ. degli Studi di Milano (Italy)


Published in SPIE Proceedings Vol. 5293:
Color Imaging IX: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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