An Improved morphological component analysis algorithm for Tangka image inpainting

doi:10.1109/CISP.2013.6744016

	An Improved morphological component analysis algorithm for Tangka image inpainting
	Hu, Wen-Jin; Li, Zhan-Ming; Liu, Zhong-Min
	2013
会议名称	2013 6th International Congress on Image and Signal Processing, CISP 2013
会议录名称	Proceedings of the 2013 6th International Congress on Image and Signal Processing, CISP 2013
卷号	1
页码	346-351
会议日期	December 16, 2013 - December 18, 2013
会议地点	Hangzhou, China
出版者	IEEE Computer Society
摘要	This paper proposed a new image inpainting method based on morphological component analysis that is capable of filling in holes in overlapping texture and cartoon layers. Firstly, due to rich content and complex color of Tangka image, the imposition of a total variation penalty by conventional model may not be accurate and easy to produce staircase. To improve the performance of sparse-representation-based image decomposition, in this paper the concept of non-local means which explicitly exploits self-similarities is introduced. In addition to, using fast algorithm reduce effectively the calculation of not related pixel weights within area, so the complexity of algorithm is reduced. The novel model preserve the fine structure, details and texture and eliminate staircase simultaneously, which make the subsequent iteration is more effective. Secondly, in order to improve the performance of sparse representation based image restoration, the concept of an example patches-aided dictionary learning algorithm named KSVD algorithm is adopted. Experimental results for thangka image which contains scratch and block loss show that the proposed method achieves better inpainting effect. © 2013 IEEE.
关键词	Computational complexity Image analysis Image denoising Image reconstruction Iterative methods Learning algorithms Stairs Textures Complexity of algorithm Conventional modeling Dictionary learning algorithms Fast algorithms Image Inpainting Morphological component analysis Non-local means Sparse representation
DOI	10.1109/CISP.2013.6744016
收录类别	EI
语种	英语
EI入藏号	20141117463596
EI主题词	Image enhancement
来源库	Compendex
分类代码	402 Buildings and Towers - 716.1 Information Theory and Signal Processing - 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 921.6 Numerical Methods
引用统计	无
文献类型	会议论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/117515
专题	电气工程与信息工程学院
作者单位	College of Electrical and Information Engineering, School of Math and Computer Science, Lanzhou University of Technology, Lanzhou, China
第一作者单位	兰州理工大学
推荐引用方式 GB/T 7714	Hu, Wen-Jin,Li, Zhan-Ming,Liu, Zhong-Min. An Improved morphological component analysis algorithm for Tangka image inpainting[C]:IEEE Computer Society,2013:346-351.