Restoration of space-variant blurred image using a wavelet transform

Shoichi Hashimoto, Hideo Saito

Research output: Contribution to journalArticlepeer-review


This paper proposes a method to reconstruct a space-variant blurred image by using the wavelet transform, which is an orthogonal transform producing space-variant frequency data. A blurred image is divided into multiple resolutions by using a wavelet transform. As each resolution depends on the position of the image, this is corrected by applying a coefficient determined by a PSF parameter (the half-maximum width) so that the position-dependent frequency data are restored. The PSF in the blurred image is estimated to realize blind deconvolution. The method has been tested by a computer simulation and by a CCD camera using real images. The results show that the PSF in the blurred images can be estimated accurately when the images contain little noise. When the resolution of each blurred image is corrected by the estimated PSF parameter, it has been confirmed that the restoration was carried out depending on the degree of blurring.

Original languageEnglish
Pages (from-to)76-84
Number of pages9
JournalSystems and Computers in Japan
Issue number14
Publication statusPublished - 1996 Dec


  • Image restoration
  • Multiresolution representation
  • Point spread function
  • Space variance
  • Wavelet transform

ASJC Scopus subject areas

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


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