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CHEN Ke, ZHU Qing-xin, YI Tao. Blind Image Restoration Using LCNN with Sparse Penalty[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 926-929.
Citation: CHEN Ke, ZHU Qing-xin, YI Tao. Blind Image Restoration Using LCNN with Sparse Penalty[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 926-929.
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Blind Image Restoration Using LCNN with Sparse Penalty

  • 1.

    School of Computer Science and Engineering,University of Electronic Science and Technology of China Chengdu 610054;

  • 2.

    No. 30 Institute,China Electronic Technology Corporation Chengdu 610041

  • Received Date: 2007-06-07
  • Rev Recd Date: 2008-03-15
  • Publish Date: 2008-12-15
  • In order to improve sparsity and robustness, a novel sparse penalty function based on smoothly clipped absolute diviation (SCAD) is proposed and applied to Lagrange Constraint Neural Network (LCNN). This method can solve ill-conditioned problem and improve sparsity, stability, and accuracy in blind image restoration. Both artificial and real-world data are calculated under some different restoration methods. Results of the experiments show that Lagrange constraint neural network with sparse penalty has better restoration effect.
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  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Blind Image Restoration Using LCNN with Sparse Penalty

  • 1. School of Computer Science and Engineering,University of Electronic Science and Technology of China Chengdu 610054;
  • 2. No. 30 Institute,China Electronic Technology Corporation Chengdu 610041
  • Received Date: 2007-06-07
  • Rev Recd Date: 2008-03-15
  • Publish Date: 2008-12-15

Abstract: In order to improve sparsity and robustness, a novel sparse penalty function based on smoothly clipped absolute diviation (SCAD) is proposed and applied to Lagrange Constraint Neural Network (LCNN). This method can solve ill-conditioned problem and improve sparsity, stability, and accuracy in blind image restoration. Both artificial and real-world data are calculated under some different restoration methods. Results of the experiments show that Lagrange constraint neural network with sparse penalty has better restoration effect.

CHEN Ke, ZHU Qing-xin, YI Tao. Blind Image Restoration Using LCNN with Sparse Penalty[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 926-929.
Citation: CHEN Ke, ZHU Qing-xin, YI Tao. Blind Image Restoration Using LCNN with Sparse Penalty[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 926-929.
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