Multichannel restoration of single channel images using a wavelet decomposition

Mark R. Banham*, Hector Gonzalez, Nikolas P. Galatsanos, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

12 Scopus citations

Abstract

In this paper, multichannel linear filtering is applied to the restoration of single channel images through the use of a wavelet decomposition. A new matrix structure for the separable 2-D wavelet transform is presented which allows the transformation of block circulant operators, found in 2-D linear filtering problems, into semi-block circulant operators, which are defined here. These operators are easily treated as block diagonal matrices in the wavelet-frequency domain. An adaptive Wiener filter is implemented in this domain, which utilizes the cross correlations between subbands in the decomposition to substantially improve the restoration of noisy-blurred images over that found with single channel filtering. This improvement is especially evident when the power spectrum of the original image is available.

Original languageEnglish (US)
Title of host publicationImage and Multidimensional Signal Processing
PublisherPubl by IEEE
Volume5
ISBN (Print)0780309464
StatePublished - Jan 1 1993
EventIEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) - Minneapolis, MN, USA
Duration: Apr 27 1993Apr 30 1993

Other

OtherIEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5)
CityMinneapolis, MN, USA
Period4/27/934/30/93

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Acoustics and Ultrasonics

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