An adaptive graininess suppression method for restoration of color degraded images

Seiki Yoshimori, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Previous studies of image restoration for noise images were based on a mask processing. These conventional noise removal methods based on the mask processing have an issue of defining degradation to accompany a spacial processing. In this paper, we propose a graininess suppression method based on edge shape. In this method, we detect edges from an noise image and perform graininess suppression for this image based on edge information. On the edge detection, we execute an image transformation for an image that enables us to extract edge by making principal component images. Moreover, we use the canny edge detection operator with can detect a weak edge that relates to a real edge, and do not detect a lie edge. In the suppression process,we use Wiener filter that can restore an noise image without making a complete edge map and the original signal map. We demonstrated the effectiveness of the present method for the noise added images and confirmed it by means of computer simulation.

Original languageEnglish
Pages (from-to)2093-2100+19
JournalIEEJ Transactions on Electronics, Information and Systems
Issue number12
Publication statusPublished - 2007
Externally publishedYes


  • Edge detection
  • Graininess suppression
  • Simple PCA
  • Wiener filter

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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