中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 机器人学研究室  > 期刊论文
题名: Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment
作者: Chen XA(陈希爱); Han Z(韩志); Wang, Yao; Tang YD(唐延东); Yu HB(于海斌)
作者部门: 机器人学研究室
通讯作者: 韩志
关键词: low-rank decomposition ; nonconvex relaxation ; quadratic penalized ; batch image alignment ; sparse or nonsparse noise
刊名: Science China Information Sciences
ISSN号: 1674-733X
出版日期: 2016
卷号: 59, 期号:5, 页码:1-13
收录类别: SCI ; EI ; CSCD
产权排序: 1
项目资助者: National Natural Science Foundation of China (Grant Nos. 61303168, 61333019).
摘要: This paper proposes a general method for dealing with the problem of recovering the low-rank structure, in which the data can be deformed by some unknown transformations and corrupted by sparse or nonsparse noises. Nonconvex penalization method is used to remedy the drawbacks of existing convex penalization method and a quadratic penalty is further used to better tackle the nonsparse noises in the data. We exploits the local linear approximation (LLA) method for turning the resulting nonconvex penalization problem into a series of weighted convex penalization problems and these subproblems are efficiently solved via the augmented Lagrange multiplier (ALM). Besides comparing with the method of robust alignment by sparse and low-rank decomposition for linearly correlated images (RASL), we also propose a nonconvex penalized lowrank and sparse decomposition (NLSD) model as comparison. Numerical experiments are conducted on both controlled and uncontrolled data to demonstrate the outperformance of the proposed method over RASL and NLSD.
语种: 英语
WOS记录号: WOS:000375885400015
WOS标题词: Science & Technology ; Technology
类目[WOS]: Computer Science, Information Systems
关键词[WOS]: VARIABLE SELECTION ; ORACLE PROPERTIES ; CONCAVE ; COMPLETION ; MATRIX ; LASSO
研究领域[WOS]: Computer Science
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/17735
Appears in Collections:机器人学研究室_期刊论文

Files in This Item: Download All
File Name/ File Size Content Type Version Access License
Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment.pdf(2764KB)期刊论文作者接受稿开放获取View Download

Recommended Citation:
Chen XA,Han Z,Wang, Yao,et al. Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment[J]. Science China Information Sciences,2016,59(5):1-13.
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[Chen XA(陈希爱)]'s Articles
[Han Z(韩志)]'s Articles
[Wang, Yao]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[Chen XA(陈希爱)]‘s Articles
[Han Z(韩志)]‘s Articles
[Wang, Yao]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
文件名: Nonconvex plus quadratic penalized low-rank and sparse decomposition for noisy image alignment.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace