Restoration of shift variant blurred image estimating the parameter distribution of point‐spread function

Shoichi Hashimoto, Hideo Saito

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

This paper describes a method of restoring a position‐dependent (shift variant) blurred image by estimating the size of the blurred part and by adjusting the restoration proportionally to it. In this method, it is assumed that all blurred images are due to a defocussing of a lens system or accidental camera motion. If the point‐spread function (PSF) of the blurred point is known, the estimation of the PSF can be replaced by the estimation of its parameter distribution (consisting of the diameter of a defocussed circle and the width of the motion caused by the accidental camera motions). Then a blind deconvolution of a shift‐variant blurred image can be realized by locally applying a Wiener filter to the estimated distribution. The method was tested using computer simulated images and actual images taken by a CCD camera, both with blurred parts. The results confirm the effectiveness of the method.

Original languageEnglish
Pages (from-to)62-72
Number of pages11
JournalSystems and Computers in Japan
Volume26
Issue number1
DOIs
Publication statusPublished - 1995

Keywords

  • Blind deconvolution
  • Blurred image
  • Image restoration
  • Shift variance
  • Wiener filter

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics

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