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A method for structured linear total least norm on blind deconvolution problem

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Abstract

The regularized structured total least norm (RSTLN) method finds an approximate solutionx and error matrixE to the overdetermined linear system (H+E)x≈b, preserving structure ofH. A new separation scheme by parts of variables for the regularized structured total least norm on blind deconvolution problem is suggested. A method combining the regularized structured total least norm method with a separation by parts of variables can be obtain a better approximated solution and a smaller residual. Computational results for the practical problem with Block Toeplitz with Toeplitz Block structure show the new method ensures more efficiency on image restoration.

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Authors and Affiliations

  1. Department of Mathematics, Chungnam National University, 305-764, Daejeon, Korea

    SeYoung Oh & SunJoo Kwon

  2. Department of Mathematics, Institute for Basic Sciences & College of Natural Sciences, Chungbuk National University, 361-763, Cheongju, Korea

    Jae Heon Yun

Authors
  1. SeYoung Oh
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  2. SunJoo Kwon
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  3. Jae Heon Yun
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Corresponding author

Correspondence to Jae Heon Yun.

Additional information

SeYoung Oh received M. Sc. from Seoul National University and Ph. D at University of Minnesota. Since 1992 he has been at Chungnam National University. His research interests include numerical optimization and biological computation.

SunJoo Kwon received M. Sc. and Ph. D from Chungnam National University. Her research interest include, numerical analysis, numerical optimization, and image restoration.

Jae Heon Yun received M. Sc. from Kyungpook National University, and Ph. D. from Iowa State University. He is currently a professor at Chungbuk National University since 1991. His research interests are computational mathematics, iterative method and parallel computation.

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Oh, S., Kwon, S. & Yun, J.H. A method for structured linear total least norm on blind deconvolution problem. JAMC 19, 151–164 (2005). https://doi.org/10.1007/BF02935795

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  • DOI: https://doi.org/10.1007/BF02935795

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