| Paper: | SPTM-P10.2 | ||
| Session: | Multirate Systems and Denoising | ||
| Time: | Thursday, May 20, 15:30 - 17:30 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Multi-rate Signal Processing & Wavelets | ||
| Title: | IMAGE DENOISING USING NEIGHBOURING WAVELET COEFFICIENTS | ||
| Authors: | Guangyi Chen; Concordia University | ||
| Tien D. Bui; Concordia University | |||
| Adam Krzyzak; Concordia University | |||
| Abstract: | The denoising of a natural image corrupted by Gaussian noise is a classical problem in signal or image processing. Donoho and his coworkers at Stanford pioneered a wavelet denoising scheme by thresholding the wavelet coefficients arising from the standard discrete wavelet transform. This work has been widely used in science and engineering applications. However, this denoising scheme tends to kill too many wavelet coefficients that might contain useful image information.In this paper, we propose one wavelet image thresholding scheme by incorporating neighbouring coefficients, namely NeighShrink. This approach is valid because a large wavelet coefficient will probably have large wavelet coefficients as its neighbours. Experimental results show that NeighShrink is better than the Wiener filter and the conventional wavelet denoising approaches: VisuShrink and SUREShrink. We also investigate different neighbourhood sizes and find that a size of 3x3 is the best among all window sizes. | ||
| Back | |||
Home -||-
Organizing Committee -||-
Technical Committee -||-
Technical Program -||-
Plenaries
Paper Submission -||-
Special Sessions -||-
ITT -||-
Paper Review -||-
Exhibits -||-
Tutorials
Information -||-
Registration -||-
Travel Insurance -||-
Housing -||-
Workshops