Multi-Cue Illumination Estimation via a Tree-Structured Group Joint Sparse Representation

doi:10.1007/s11263-015-0844-7

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	Multi-Cue Illumination Estimation via a Tree-Structured Group Joint Sparse Representation
	Li, Bing1 ; Xiong, Weihua 1; Hu, Weiming1 ; Funt, Brian 2; Xing, Junliang1
发表期刊	INTERNATIONAL JOURNAL OF COMPUTER VISION
	2016-03-01
卷号	117 期号:1 页码:21-47
文章类型	Article
摘要	A multi-cue illumination estimation method based on tree-structured group joint sparse representation is proposed. Tests show that the proposed method works better than existing methods, most of which are based on using only a single cue type, for example, a binarized color histogram or simple image statistic such as the mean RGB. Most existing illumination estimation methods make their estimates using only one of three kinds of cues. They differ in which cue type they use, but the chosen cue is either based on (1) properties of the low-level RGB color distribution, (2) mid-level initial illuminant estimates provided by subordinate methods, or (3) high-level knowledge of scene content (e.g., indoor versus outdoor scene). The proposed multi-cue method combines the information provided by cues of all three of these types within the framework of a tree-structured group joint sparse representation (TGJSR). In TGJSR, the training data is grouped into a tree of subgroups. A test image under an unknown illuminant has its features reconstructed in terms of a joint sparse representation model derived from the grouped training data. The test image's illumination is then estimated based on the weights involved in the joint sparse representation model. As a general framework, the proposed TGJSR framework can also easily be extended to incorporate any new features or cues that might be discovered in the future for illumination estimation.
关键词	Color Constancy Illumination Estimation Automatic White Balancing Tree-structured Group Sparse Representation
WOS标题词	Science & Technology ; Technology
DOI	10.1007/s11263-015-0844-7
关键词[WOS]	COLOR CONSTANCY ALGORITHMS ; CHROMATICITY ; STATISTICS ; IMAGES
收录类别	SCI
语种	英语
项目资助者	National Nature Science Foundation of China(61370038 ; 973 Basic Research Program of China(2014CB349303) ; Chinese National Programs for High Technology Research and Development (863 Program)(2012AA012503 ; Natural Sciences and Engineering Research Council of Canada ; 61472421) ; 2012AA012504)
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000371156500002
引用统计	被引频次：21[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11101
专题	多模态人工智能系统全国重点实验室_视频内容安全
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Simon Fraser Univ, Sch Comp Sci, Burnaby, BC V5A 1S6, Canada
第一作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Li, Bing,Xiong, Weihua,Hu, Weiming,et al. Multi-Cue Illumination Estimation via a Tree-Structured Group Joint Sparse Representation[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2016,117(1):21-47.
APA	Li, Bing,Xiong, Weihua,Hu, Weiming,Funt, Brian,&Xing, Junliang.(2016).Multi-Cue Illumination Estimation via a Tree-Structured Group Joint Sparse Representation.INTERNATIONAL JOURNAL OF COMPUTER VISION,117(1),21-47.
MLA	Li, Bing,et al."Multi-Cue Illumination Estimation via a Tree-Structured Group Joint Sparse Representation".INTERNATIONAL JOURNAL OF COMPUTER VISION 117.1(2016):21-47.

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