@inproceedings{7d11129877434f47a3f47badb4c8cc11,
title = "Lighting alignment for image sequences",
abstract = "Lighting is one of the challenges for image processing. Even though some algorithms are proposed to deal with the lighting variation for images, most of them are designed for a single image but not for image sequences. In fact, the correlation between frames can provide useful information to remove the illumination diversity, which is not available for a single image. In this paper, we proposed a 2-step lighting alignment algorithm for image sequences. Based on entropy, a perception-based lighting model is initialized according to the lighting condition of first frame. Then the difference between frames is applied to optimize the parameters of the lighting model and consequently the lighting conditions can be aligned for the sequence. At the same time, the local features of each frame can be enhanced. Experimental results show the effectiveness of the proposed algorithm.",
keywords = "Entropy-based model, Lighting alignment, Perceptionbased model, Tracking",
author = "Xiaoyue Jiang and Xiaoyi Feng and Jun Wu and Jinye Peng",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 8th International Conference on Image and Graphics, ICIG 2015 ; Conference date: 13-08-2015 Through 16-08-2015",
year = "2015",
doi = "10.1007/978-3-319-21963-9_43",
language = "英语",
isbn = "9783319219622",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "462--474",
editor = "Yu-Jin Zhang",
booktitle = "Image and Graphics - 8th International Conference, ICIG 2015, Proceedings",
}