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<item>
  <id>05357875</id>
  <dt>j</dt>
  <an>05357875</an>
  <augroup>
    <au>Xu, Jing</au>
    <au>Chang, Qian-shun</au>
  </augroup>
  <ti>A robust algorithm for blind total variation restoration.</ti>
  <so>Acta Math. Appl. Sin., Engl. Ser. 24, No. 4, 681-690 (2008).</so>
  <py>2008</py>
  <pu>Chinese Mathematical Society, Beijing; Springer, Heidelberg</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>blind deconvolution</ut>
    <ut>total variation</ut>
    <ut>algebraic multigrid method</ut>
    <ut>Krylov acceleration</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1007/s10255-007-7120-8</li>
  </ligroup>
  <abgroup>
    <ab>Summary: Image restoration is a fundamental problem in image processing. Blind image restoration has a great value in its practical application. However, it is not an easy problem to solve due to its complexity and difficulty. In this paper, we combine our robust algorithm for known blur operator with an alternating minimization implicit iterative scheme to deal with blind deconvolution problem, recover the image and identify the point spread function(PSF). The only assumption needed is satisfy the practical physical sense. Numerical experiments demonstrate that this minimization algorithm is efficient and robust over a wide range of PSF and have almost the same results compared with known PSF algorithm.</ab>
    <rv></rv>
  </abgroup>
</item>