文献类型：会议论文

英文题名：Ilumination Estimation Combining Physical and Statistical Approaches

作者：Yuan Jia-zheng[1];Tian Li-yan[2];Bao Hong[1];Huang Jing-hua[1];Zhang Rui-zhe[1]

第一作者：Yuan Jia-zheng

通讯作者：Yuan, JZ[1]

机构：[1]Beijing Union Univ, Inst Informat Technol, Beijing 100101, Peoples R China;[2]Union Univ, Coll Appl Sci & Technol, Beijing 100101, Peoples R China

第一机构：北京联合大学智慧城市学院

通讯机构：[1]corresponding author), Beijing Union Univ, Inst Informat Technol, Beijing 100101, Peoples R China.|[1141734]北京联合大学智慧城市学院;[11417]北京联合大学;

会议论文集：3rd International Symposium on Intelligent Information Technology Application

会议日期：NOV 21-22, 2009

会议地点：Nanchang, PEOPLES R CHINA

语种：英文

外文关键词：Illumination estimation; Color constancy; K-nearest-neighbor; Feature extraction; IE-KNN

摘要：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.