Letters: Noise removal using a novel non-negative sparse coding shrinkage technique

  • Authors:

  • Li Shang;De-Shuang Huang;Chun-Hou Zheng;Zhan-Li Sun

  • Affiliations:

  • Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, P.O. Box 1130, Hefei, Anhui 230031, China and Department of Automation, University of Science and Technology of China, Hefei, ...;Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, P.O. Box 1130, Hefei, Anhui 230031, China;Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, P.O. Box 1130, Hefei, Anhui 230031, China and Department of Automation, University of Science and Technology of China, Hefei, ...;Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, P.O. Box 1130, Hefei, Anhui 230031, China and Department of Automation, University of Science and Technology of China, Hefei, ...

  • Venue:
  • Neurocomputing
  • Year:
  • 2006

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Abstract

A novel and successful method for denoising natural images using an extended non-negative sparse coding (NNSC) shrinkage technique is proposed. The main idea is to utilize the selected shrinkage function to the non-negative sparse components to remove noises hidden in an image. This method is evaluated by values of the normalized mean squared error (MSE) and signal to noise ratio (SNR). Compared with other denoising methods, the simulation results show that the NNSC shrinkage technique is indeed effective and efficient.