Abstract
In this paper, we propose a novel hierarchical statistical model for image wavelet coefficients. A simple classification scheme is used to construct a model that captures interscale and intrascale dependencies of wavelet coefficients. Applications to image denoising are presented. We develop a simple algorithm that outperforms other wavelet denoising schemes that exploit first-order statistics, or inter- or intra- scale dependencies alone.
| Original language | English (US) |
|---|---|
| Pages | 386-390 |
| Number of pages | 5 |
| State | Published - 1999 |
| Event | International Conference on Image Processing (ICIP'99) - Kobe, Jpn Duration: Oct 24 1999 → Oct 28 1999 |
Other
| Other | International Conference on Image Processing (ICIP'99) |
|---|---|
| City | Kobe, Jpn |
| Period | 10/24/99 → 10/28/99 |
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering