Title
A Variational Framework For Retinex
Abstract
Retinex theory addresses the problem of separating the illumination from the reflectance in a given image and thereby compensating for non-uniform lighting. This is in general an ill-posed problem. In this paper we propose a variational model for the Retinex problem that unifies previous methods. Similar to previous algorithms, it assumes spatial smoothness of the illumination field. In addition, knowledge of the limited dynamic range of the reflectance is used as a constraint in the recovery process. A penalty term is also included, exploiting a-priori knowledge of the nature of the reflectance image. The proposed formulation adopts a Bayesian view point of the estimation problem, which leads to an algebraic regularization term, that contributes to better conditioning of the reconstruction problem.Based on the proposed variational model, we show that the illumination estimation problem can be formulated as a Quadratic Programming optimization problem. An efficient multi-resolution algorithm is proposed. It exploits the spatial correlation in the reflectance and illumination images. Applications of the algorithm to various color images yield promising results.
Year
DOI
Venue
2002
10.1117/12.469539
HUMAN VISION AND ELECTRONIC IMAGING VII
Keywords
Field
DocType
computer programming,reflectivity,algorithms
Color constancy,Mathematical optimization,Spatial correlation,Optical engineering,Regularization (mathematics),Quadratic programming,Smoothness,Optimization problem,Mathematics,Computer programming
Conference
Volume
ISSN
Citations 
4662
0277-786X
20
PageRank 
References 
Authors
1.70
0
5
Name
Order
Citations
PageRank
ron kimmel1201.70
Michael Elad211274854.93
Doron Shaked355355.76
Renato Keshet433827.26
irwin sobel5201.70