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.

Underwater color constancy: enhancement of automatic live fish recognition / M. Chambah, A. Renouf, D. Semani, P. Courtellemont, A. Rizzi (PROCEEDINGS OF SPIE, THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING). - In: Color Imaging IX: Processing, Hardcopy, and Applications / [a cura di] R. Eschbach, G.G. Marcu. - [s.l] : SPIE, 2004. - ISBN 0-8194-5196-7. - pp. 157-168 (( convegno Electronic Imaging tenutosi a San Jose nel 2004 [10.1117/12.524540].

Underwater color constancy: enhancement of automatic live fish recognition

A. Rizzi
Ultimo
2004

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.
Automatic color correction; Automatic fish species recognition; Color constancy; Color features; Color pattern recognition; Underwater imaging
Settore INF/01 - Informatica
2004
SPIE
IS&T
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/192181
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