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논문검색

Sparse Representation based Satellite Image Restoration Using Adaptive Reciprocal Cell

초록

영어

Recently, an emerging method called image sparse representation has attracted more attentions. The method has been proved to be effective in various image processing applications. It is important to note that few sparse representation methods fail to analyze the aliasing in satellite image restoration. To address the problem, firstly, we employ adaptive reciprocal cell as a image quality estimation tool, which can analyze the satellite image degradation factors including aliasing, blur and noise. Then, with the help of the powerful tool, the estimation about the satellite image quality is introduced into the sparse representation model . Experiment results show that our method can produce good quality restored results.

목차

Abstract
 1. Introduction
 2. Proposed Method
  2.1. Adaptive Reciprocal Cell
  2.2. Adaptive Reciprocal Cell based Sparse Representation Model
 3. Experimental Results
 4. Discussions
 Acknowledgments
 References

저자정보

  • Yanfei He Department of Math and Statistic, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Jianwei Zhang Department of Math and Statistic, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Shunfeng Wang Department of Math and Statistic, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Yuhui Zheng School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Jin Wang School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Yunjie Chen Department of Math and Statistic, Nanjing University of Information Science & Technology, Nanjing 210044, China

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