Abstract
In this paper, we address the problem of restoring an image from its noisy convolutions with two or more unknown blur functions. We extend some of the results developed for the multichannel blind deconvolution problem in one dimension. When the unknown blur functions have no common factors, we present algorithms to estimate them quickly and accurately. Once the blur functions are available, they can be used to reconstruct the unknown image. We show that, under certain conditions, the last step can be achieved by FIR filtering with a perfect reconstruction filter bank. Some results on the effects of noise on these algorithms are also presented.
| Original language | English (US) |
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| Title of host publication | IEEE International Conference on Image Processing |
| Editors | Anon |
| Publisher | IEEE |
| Pages | 97-100 |
| Number of pages | 4 |
| Volume | 3 |
| State | Published - 1996 |
| Event | Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) - Lausanne, Switz Duration: Sep 16 1996 → Sep 19 1996 |
Other
| Other | Proceedings of the 1996 IEEE International Conference on Image Processing, ICIP'96. Part 2 (of 3) |
|---|---|
| City | Lausanne, Switz |
| Period | 9/16/96 → 9/19/96 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Hardware and Architecture
- Electrical and Electronic Engineering