llumination Estimation Combining Physical and Statistical Approaches

Illumination estimation for color constancy is an important problem in computer vision. Existing algorithms can be divided into two groups: physics-based algorithms and statistics-based approaches. In this paper, the advantages of the two kinds are integrated. At first, a novel statistic-based algorithm called Illumination Estimation using K-nearest-neighbor (IE-KNN) is proposed. And then the physics-based Grey-Edge algorithm is used to extract image features for IE-KNN. One of the most important aims of this paper is to reduce the feature dimension in traditional statistics-based approaches. The experimental results show that this combined physical and statistical algorithm is effective and can achieved much better color constancy result.