Blind Separation of Permuted Alias Image with Morphological Diversity Based on NSCT and Waveatom Dictionary

X.T. Duan; P. Zhu; S.J. Li; Z. J. Zhang; Y. J. Yang

Blind Separation of Permuted Alias Image with Morphological Diversity Based on NSCT and Waveatom Dictionary

원문정보

X.T. Duan, P. Zhu, S.J. Li, Z. J. Zhang, Y. J. Yang

보안공학연구지원센터(IJSIP) International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.8 No.11 2015.11 pp.111-118

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초록

영어

A blind separation algorithm was proposed for the type of permuted alias images with morphological diversity in this paper. Firstly, permuted alias image mode in sparse domain was presented and separation scheme based on sparse domain was proposed. Non-subsampled Contourlet transform and Waveatom transform are respectively used as two type of dictionaries for piecewise cartoon and texture image. Then the permuting image can be separated from permuted alias image by morphological component analysis algorithm. The results show that our algorithm can separate effectively texture image from the permuted alias image not being affected by size, location number and types of texture image for a permuted alias image composed by piecewise smooth part and texture part.

Abstract
1. Introduction
2. Separation Mode of Permuted Alias Image and Permuted Alias Image Mode in Sparsity Domain
  2.1. Separation Mode of Permuted Alias Image Mode
  2.2. Permuted Alias Image Mode in Sparsity Domain
3. Separation of the Permuted Alias Image and Selection of Dictionary
  3.1. Separation of the Permuted Alias Image
  3.2. Separation Selection of Dictionary
4. Results and Discussion
5. Conclusions
References

키워드

저자정보

X.T. Duan School of Computer and Information Engineering, Henan Normal University, Henan, China, Engineering Technology Research Center for Computing Intelligence & Data Mining, Henan Province
P. Zhu Modern Educational Technology Center, Shanghai University of Electric Power, Shanghai, China
S.J. Li College of Physics and Electronic Engineering, Henan Normal University, Henan, China
Z. J. Zhang School of Computer and Information Engineering, Henan Normal University, Henan, China, Engineering Technology Research Center for Computing Intelligence & Data Mining, Henan Province
Y. J. Yang School of Computer and Information Engineering, Henan Normal University, Henan, China, Engineering Technology Research Center for Computing Intelligence & Data Mining, Henan Province

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