Color and illuminant voting

被引：44

作者：

Sapiro, G ^{[1
]}

机构：

[1] Univ Minnesota, Dept Elect & Comp Engn, Minneapolis, MN 55455 USA

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 1999年 / 21卷 / 11期

基金：

美国国家科学基金会;

关键词：

physics-based vision; color constancy; illuminant estimation; Hough transform; physical constraints; bilinear models;

D O I：

10.1109/34.809114

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A geometric-vision approach to color constancy and illuminant estimation is presented in this paper. We show a general framework, based on ideas from the generalized probabilistic Hough transform, to estimate the illuminant and reflectance of natural images. Each image pixel "votes" for possible illuminants and the estimation is based on cumulative votes. The framework is natural for the introduction of physical constraints in the color constancy problem. We show the relationship of this work to previous algorithms for color constancy and present examples.

引用

页码：1210 / 1215

页数：6

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