Video-based illumination estimation

Authors:
Ning Wang;Brian Funt;Congyan Lang;De Xu
Affiliations:
School of Computer Science and Infromation Technology, Beijing Jiaotong University, Beijing, China and School of Computing Science, Simon Fraser University, Burnaby, B.C, Canada;School of Computing Science, Simon Fraser University, Burnaby, B.C, Canada;School of Computer Science and Infromation Technology, Beijing Jiaotong University, Beijing, China;School of Computer Science and Infromation Technology, Beijing Jiaotong University, Beijing, China
Venue:
CCIW'11 Proceedings of the Third international conference on Computational color imaging
Year:
2011

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Abstract

One possible solution to estimating the illumination for color constancy and white balance in video sequences would be to apply one of the many existing illumination-estimation algorithms independently to each video frame. However, the frames in a video are generally highly correlated, so we propose a video-based illumination-estimation algorithm that takes advantage of the related information between adjacent frames. The main idea of the method is to cut the video clip into different 'scenes.' Assuming all the frames in one scene are under the same (or similar) illuminant, we combine the information from them to calculate the chromaticity of the scene illumination. The experimental results showed that the proposed method is effective and outperforms the original single-frame methods on which it is based.