Illumination Chromaticity Estimation using Inverse-Intensity Chromaticity Space

Existing color constancy methods cannot handle both uniform colored surfaces and highly textured surfaces in a single integrated framework. Statistics-based methods require many surface colors, and become error prone when there are only few surface colors. In contrast, dichromaticbased methods can successfully handle uniformly colored surfaces, but cannot be applied to highly textured surfaces since they require precise color segmentation. In this paper, we present a single integrated method to estimate illumination chromaticity from single/multi-colored surfaces. Unlike the existing dichromatic-based methods, the proposed method requires only rough highlight regions, without segmenting the colors inside them. We show that, by analyzing highlights, a direct correlation between illumination chromaticity and image chromaticity can be obtained. This correlation is clearly described in "inverse-intensity chromaticity space", a new two-dimensional space we introduce. In addition,...

• Type: Conference
• Year: 2003
• Where: CVPR
• Authors: Robby T. Tan, Ko Nishino, Katsushi Ikeuchi
• Keywords: Computer Vision, CVPR 2003, Illumination Chromaticity, Image Chromaticity, Inverse-intensity Chromaticity Space, Textured Surfaces, Uniform Colored Surfaces