Stitching contaminated images

doi:10.1016/j.neucom.2016.07.004

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Stitching contaminated images
	Li, Chuan1 ; Liu, Zhi-Yong1,2,3 ; Yang, Xu1 ; Qiao, Hong1,2,3 ; Su, Jian-Hua1 ; Zhi-Yong Liu
发表期刊	NEUROCOMPUTING
	2016-11-19
卷号	214 期号:no 页码:829-836
文章类型	Article
摘要	; Image stitching has long been studied in computer vision and has been applied to many fields. However, when the input images contain moving objects and meanwhile are noisy or partially contaminated, it remains a challenge to get a satisfactory clean panorama. In this paper, we propose to tackle both the challenges, i.e., denoising and stitching, by proposing a new energy function in a unified way. Such an energy model is however non-submodule, making the widely used optimization algorithms, such as graph cuts, hard to be used directly. We then generalize the recently proposed Graduated Non-Convexity and Concavity Procedure (GNCCP) to approximately minimize the energy. Comparative experiments validate the efficacy of the proposed energy function on both image denoising and stitching. Besides, the results also show the validity of the generalized-GNCCP on minimizing non-submodule function. (C) 2016 Elsevier B.V. All rights reserved.
关键词	Image Stitching Denoising Energy Minimization Gnccp
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.neucom.2016.07.004
关键词[WOS]	GRAPH CUTS ; FEATURES
收录类别	SCI
语种	英语
项目资助者	National Foundation of Science of China (NFSC)(61375005 ; Ministry of Science and Technology of China (MOST)(2015BAK35B00 ; Department of Science and Technology of Guangdong(2016B090910001) ; 61033011) ; 2015BAK35B01)
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000386741300078
引用统计	被引频次：11[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/173211/12600
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Zhi-Yong Liu
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China 3.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Li, Chuan,Liu, Zhi-Yong,Yang, Xu,et al. Stitching contaminated images[J]. NEUROCOMPUTING,2016,214(no):829-836.
APA	Li, Chuan,Liu, Zhi-Yong,Yang, Xu,Qiao, Hong,Su, Jian-Hua,&Zhi-Yong Liu.(2016).Stitching contaminated images.NEUROCOMPUTING,214(no),829-836.
MLA	Li, Chuan,et al."Stitching contaminated images".NEUROCOMPUTING 214.no(2016):829-836.

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