Abstract
We describe a statistical model for images decomposed in an overcomplete wavelet pyramid. Each neighborhood of pyramid coefficients is modeled as the product of a Gaussian vector of known covariance, and an independent hidden positive scalar random variable. We propose an efficient Bayesian estimator for the pyramid coefficients of an image degraded by linear distortion (e.g., blur) and additive Gaussian noise. We demonstrate the quality of our results in simulations over a wide range of blur and noise levels.
| Original language | English (US) |
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| Pages | 965-968 |
| Number of pages | 4 |
| State | Published - 2003 |
| Event | Proceedings: 2003 International Conference on Image Processing, ICIP-2003 - Barcelona, Spain Duration: Sep 14 2003 → Sep 17 2003 |
Other
| Other | Proceedings: 2003 International Conference on Image Processing, ICIP-2003 |
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| Country/Territory | Spain |
| City | Barcelona |
| Period | 9/14/03 → 9/17/03 |
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering