Underwater Color Constancy : Enhancement of Automatic Live Fish Recognition

M. Chambah (1, 2) , D. Semani (1, 2) , Arnaud Renouf (3) , P. Coutellemont (1, 2) , A. Rizzi (1, 2)

1 GREYC - Groupe de Recherche en Informatique, Image et Instrumentation de Caen
2 L3I - Laboratoire Informatique, Image et Interaction - EA 2118
3 Equipe Image - Laboratoire GREYC - UMR6072

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.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

M. Chambah, D. Semani, Arnaud Renouf, P. Coutellemont, A. Rizzi. Underwater Color Constancy : Enhancement of Automatic Live Fish Recognition. 16th Annual symposium on electronic imaging, 2004, Inconnue, United States. pp.157-168. ⟨hal-00263734⟩