Name
Abstract | ||
|---|---|---|
ABSTRACT In this paper a denoising technique for digital gray value images corrupted with additive Gaussian noise is presented. We studied a recently proposed hard thresholding technique which uses a two stage selection procedure in which coef- cients are selected based on their magnitude, spatial connect- edness and interscale dependencies. We construct a shrink- age version of the algorithm which outperforms,the origi- nal one. We also present a new hard thresholding algorithm which incorporates the spatial connectivity information in a more simple and efcient way and construct a shrinkage ver- sion of it. The new algorithms are faster and lead to better denoising performances compared to the original one, both visually and quantitatively. |
Year | Venue | Keywords |
|---|---|---|
2006 | EUSIPCO | awgn,image denoising,image segmentation,wavelet transforms,additive gaussian noise,digital gray image denoising technique,geometrical wavelet shrinkage approach,hard thresholding technique,spatial connectivity information,two stage selection procedure |
Field | DocType | ISSN |
Noise reduction,Magnitude (mathematics),Social connectedness,Pattern recognition,Shrinkage,Non-local means,Artificial intelligence,Thresholding,Video denoising,Gaussian noise,Mathematics | Conference | 2219-5491 |
Citations | PageRank | References |
0 | 0.34 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bruno Huysmans | 1 | 27 | 2.12 |
| Aleksandra Pi Zurica | 2 | 0 | 0.34 |
| Wilfried Philips | 3 | 1476 | 124.85 |