Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/55480
Type: | Conference paper |
Title: | Shift-invariant wavelet denoising using interscale dependency |
Author: | Chen, P. Suter, D. |
Citation: | Proceedings International Conference on Image Processing (ICIP) Volume 2, 2004: pp.1005-1008 |
Publisher: | IEEE |
Publisher Place: | Online |
Issue Date: | 2004 |
Series/Report no.: | IEEE International Conference on Image Processing (ICIP) |
ISBN: | 0780385543 |
ISSN: | 1522-4880 |
Conference Name: | IEEE International Conference on Image Processing - ICIP (2004 : Singapore) |
Statement of Responsibility: | Pel Chm mid David Sliter |
Abstract: | Using statistical modeling in the wavelet domain, we address the problem of image denoising. Despite being effective, the denoised images can suffer from the Gibbs-like artifacts, like ringing around the edges and speckles in the smooth regions. We employ shift-invariant (SI) wavelet denoising in order to reduce these unpleasant artifacts. Not only is the visual quality greatly improved but also a PSNR gain of about 0.7∼0.9 dB is obtained. The proposed approach, siPAB, outperforms siHMT, which is a competitive SI wavelet denoising approach, by 0.1∼0.5 dB. |
Description (link): | http://dx.doi.org/10.1109/ICIP.2004.1419471 |
Appears in Collections: | Aurora harvest 5 Computer Science publications |
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