Stitching contaminated images

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 机器人应用与理论组

	Stitching contaminated images
	Li, Chuan1 ; Liu, Zhi-Yong1,2,3 ; Yang, Xu1 ; Qiao, Hong1,2,3 ; Su, Jian-Hua1
刊名	NEUROCOMPUTING
	2016-11-19
卷号	214 期号:no 页码:829-836
关键词	Image stitching Denoising Energy minimization GNCCP
通讯作者	Zhi-Yong Liu
中文摘要
英文摘要	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.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence
研究领域[WOS]	Computer Science
关键词[WOS]	GRAPH CUTS ; FEATURES
收录类别	SCI
语种	英语
WOS记录号	WOS:000386741300078
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/12600]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
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
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.(2016).Stitching contaminated images.NEUROCOMPUTING,214(no),829-836.
MLA	Li, Chuan,et al."Stitching contaminated images".NEUROCOMPUTING 214.no(2016):829-836.