Color Constancy Using Stage Classification
The aim of color constancy is to remove the effect of the color of the light source. Since color constancy is inherently an ill-posed problem, different assumptions have been proposed. Because existing color constancy algorithms are based on specific assumptions, none of them can be considered as universal. Therefore, how to select a proper algorithm for a given imaging configuration is an important question. In this paper, image stage models are used to aid the selection of a specific color constancy algorithm. Image stages are 3D models of a scene. Based on stage classification, the most suitable color constancy algorithms is selected. Experiments on large scale image datasets show that the proposed algorithm using stage classification outperforms state-of-the-art single color constancy algorithms with an improvement of almost 8%.