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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qing Lu Tianzi Jiang |
| Copyright Year | 2000 |
| Description | Author affiliation: Inst. of Autom., Nat. Lab. of Pattern Recognition, China (Qing Lu) |
| Abstract | In this paper, we propose a novel pixon-based multiresolution method for image denoising. The key idea to our approach is that a pixon map is embedded into the MRF models under a Bayesian framework. The remarkable advantage of our approach over the existing works in this field is that restoring corrupted images and preserving the shape transitions in the restored results have been orchestrated very well. A simulated annealing algorithm is implemented to find the MAP solution. A lot of experiments illustrate that our method is much more effective and powerful in the noise reduction than the Wiener and median filtering techniques, two typical and widely used techniques. |
| Starting Page | 726 |
| Ending Page | 729 |
| File Size | 472634 |
| Page Count | 4 |
| File Format | |
| ISBN | 0769507506 |
| ISSN | 10514651 |
| DOI | 10.1109/ICPR.2000.903647 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-09-03 |
| Publisher Place | Spain |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Bayesian methods Image denoising Image restoration Wiener filter Simulated annealing Shape Noise reduction Image reconstruction Degradation Laboratories |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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