An Improved morphological component analysis algorithm for Tangka image inpainting | |
Hu, Wen-Jin; Li, Zhan-Ming; Liu, Zhong-Min | |
2013 | |
会议日期 | December 16, 2013 - December 18, 2013 |
会议地点 | Hangzhou, China |
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 |
卷号 | 1 |
DOI | 10.1109/CISP.2013.6744016 |
页码 | 346-351 |
英文摘要 | 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. |
会议录 | Proceedings of the 2013 6th International Congress on Image and Signal Processing, CISP 2013 |
会议录出版者 | IEEE Computer Society |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://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 |
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]. 见:. Hangzhou, China. December 16, 2013 - December 18, 2013. |
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