Abstract
Removing noise from a digital image is a challenging problem. Application of Gaussian Scale Mixtures (GSM) in the wavelet domain has been reported to be one of the most effective denoising algorithms, published to date. In this paper we investigate the impact of overcomplete wavelet image representations on the GSM image denoising algorithm. We explore the desirable local characteristics of wavelet coefficients that can enhance the efficiency of GSM denoising and based on the findings, we devise an improved over-complete pyramid representation to enhance the GSM denoising performance. We present the experimental denoising results using the proposed pyramid representation, and they outperform state-of-the-art GSM denoising results reported in the literature.
| Original language | English |
|---|---|
| Title of host publication | Electronic Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, ICME 2011 |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
| Event | 2011 12th IEEE International Conference on Multimedia and Expo, ICME 2011 - Barcelona, Spain Duration: 11 Jul 2011 → 15 Jul 2011 |
Publication series
| Name | Proceedings - IEEE International Conference on Multimedia and Expo |
|---|---|
| ISSN (Print) | 1945-7871 |
| ISSN (Electronic) | 1945-788X |
Conference
| Conference | 2011 12th IEEE International Conference on Multimedia and Expo, ICME 2011 |
|---|---|
| Country/Territory | Spain |
| City | Barcelona |
| Period | 11/07/11 → 15/07/11 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Free Keywords
- Gaussian scale mixture
- image denoising
- overcomplete transforms
- pyramid representations
- Wavelet transforms
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
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