Name
Abstract | ||
|---|---|---|
A novel kernel anisotropic diffusion (KAD) method is proposed for robust noise reduction and edge detection. The KAD incorporates a kernelized gradient operator in the diffusion, leading to more effective edge detection and providing a better control to the diffusion process. Adaptive diffusion threshold estimation and automatic diffusion termination criterion are also introduced to enhance the robustness of the KAD. The KAD outperforms several previous anisotropic diffusion-based methods for low SNR images. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1016/j.patrec.2008.03.002 | Pattern Recognition Letters |
Keywords | DocType | Volume |
novel kernel anisotropic diffusion,edge detection,effective edge detection,previous anisotropic diffusion-based method,automatic diffusion termination criterion,noise reduction,kernel methods,anisotropic diffusion,low snr image,better control,diffusion process,adaptive diffusion threshold estimation,kernelized gradient operator,kernel method | Journal | 29 |
Issue | ISSN | Citations |
10 | Pattern Recognition Letters | 29 |
PageRank | References | Authors |
1.09 | 26 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinhua Yu | 1 | 110 | 19.39 |
| Yuanyuan Wang | 2 | 498 | 82.58 |
| Yuzhong Shen | 3 | 184 | 21.96 |