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 language | English (US) |
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| Title of host publication | Image and Multidimensional Signal Processing |
| Publisher | Publ by IEEE |
| Volume | 5 |
| ISBN (Print) | 0780309464 |
| State | Published - Jan 1 1993 |
| Event | IEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) - Minneapolis, MN, USA Duration: Apr 27 1993 → Apr 30 1993 |
Other
| Other | IEEE International Conference on Acoustics, Speech and Signal Processing, Part 5 (of 5) |
|---|---|
| City | Minneapolis, MN, USA |
| Period | 4/27/93 → 4/30/93 |
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Acoustics and Ultrasonics