RESTORATION OF BLURRED IMAGES BY AN ITERATIVE ESTIMATION ALGORITHM BASED ON A TWO-DIMENSIONAL WIENER FILTER.

Takashi Yahagi, Yoichi Kato, Michio Shinozaki

Research output: Contribution to journalArticlepeer-review

Abstract

New probabilistic restoration of noisy blurred images is presented. The optimum filter minimizing mean-squared errors of restored images is derived for images with known statistical characteristics. The Wiener filter technique utilizing power spectra can be applied to yield the optimum filter. Unlike a Kalman filter, the filter is noncausal in the sense that estimation at a point depends not only on past estimates, but also on future estimates yet to be found. The problem can be solved by an iterative method proposed in this study. It is shown that the proposed filter is effective for uniformly distributed noise as well as impulsive noise.

Original languageEnglish
Pages (from-to)40-47
Number of pages8
JournalSystems, computers, controls
Volume15
Issue number1
Publication statusPublished - 1984 Jan
Externally publishedYes

ASJC Scopus subject areas

  • Engineering(all)

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