Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
권호 표지

A METHOD FOR STRUCTURED LINEAR TOTAL LEAST NORM ON BLIND DECONVOLUTION PROBLEM

  • Oh, Se-Young (Department of Mathematics, Chungnam National University) ;
  • Kwon, Sun-Joo (Department of Mathematics, Chungnam National University) ;
  • Yun, Jae-Heon (Department of Mathematics, Institute for Basic Sciences & College of Natural Sciences, Chungbuk National University)
  • Published : 2005.09.01

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Abstract

The regularized structured total least norm (RSTLN) method finds an approximate solution x and error matrix E to the overdetermined linear system (H + E)x $\approx$ b, preserving structure of H. 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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