A sparse representation denoising algorithm for visible and infrared image based on orthogonal matching pursuit

  • Zhuang Zhang
  • Xu Chen
  • Lei LiuEmail author
  • Yefei Li
  • Yubin Deng
Original Paper


The orthogonal matching pursuit algorithm directly samples the image signal by using the sparsity of the image signal. It uses the atom that matches the image signal feature to describe the image, which can better preserve the detailed features of the image. In this paper, an improvement of variable step size and optimized cut-off conditions is made. The experimental results show that the improved algorithm makes the denoised image clearer and have more detailed features.


Image denoising Sparse representation Matching pursuit 



This work is supported by Qing Lan Project of Jiangsu Province-China (Grant No. 2017-AD41779), the Fundamental Research Funds for the Central Universities-China (Grant No. 30916011206) and the Six Talent Peaks Project in Jiangsu Province-China (Grant No. 2015-XCL-008).


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Optoelectronic Technology, School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjingPeople’s Republic of China

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