Global Multiple-View Color Consistency

Pierre Moulon 1, 2, 3 Bruno Duisit 4 Pascal Monasse 1, 2, 3
1 IMAGINE [Marne-la-Vallée]
LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech
4 Mikros Image
Chercheur indépendant
Abstract : In a multiple-view image acquisition process, color consistency is not ensured. This is an important problem for image fusion tasks: object texturing or mosaics blending for example. In automatic mode, the camera adapts its settings --shutter-speed and aperture-- to the captured image content. Therefore the color of objects changes over an image sequence. In order to restore the color consistency, a transformation model between reference and observed colors have to be estimated. It introduces two main problems: the data selection (common pixels between images) and the estimation of a reliable color transformation between those pixels. While most techniques ensure only pairwise consistency and possibly proceed incrementally, we address the problem globally on the entire photo collection. We propose a global multi-view color consistency solution that in a first step selects robustly the common color information between images and in a second step estimates the color transformations that set all pictures in a common color reference, which involves a global minimization. Our compact representation enables to process large image datasets efficiently.
keyword : color consistency
Type de document :
Communication dans un congrès
CVMP, Nov 2013, Londres, United Kingdom. 2013
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Dernière modification le : jeudi 5 juillet 2018 - 14:28:35
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  • HAL Id : hal-00873517, version 1

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Pierre Moulon, Bruno Duisit, Pascal Monasse. Global Multiple-View Color Consistency. CVMP, Nov 2013, Londres, United Kingdom. 2013. 〈hal-00873517〉

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