Name
Title | ||
|---|---|---|
SAR image de-noising using local properties analysis and discrete non-separable shearlet transform |
Abstract | ||
|---|---|---|
A new SAR image de-noising approach that uses the local properties analysis of SAR image and the discrete nonseparable shearlet transform (DNST) is proposed in this paper. According to the local properties analysis method, the SAR image is divided into homogeneous region, non-homogeneous region and target region. The homogeneous region uses the average filter to de-noising. The non-homogeneous region uses the DNST transform to de-noising and target region is reserved directly. The experimental results show that the proposed approach can efficiently reduce the speckle noises and improve the edge-preserving ability. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CISP-BMEI.2017.8301960 | 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) |
Keywords | Field | DocType |
SAR image de-nosing,local properties analysis,shearlet transform | Noise reduction,Computer vision,Pattern recognition,Speckle pattern,Synthetic aperture radar,Computer science,Homogeneous,Shearlet transform,Separable space,Filter (signal processing),Image denoising,Artificial intelligence | Conference |
ISBN | Citations | PageRank |
978-1-5386-1938-4 | 0 | 0.34 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ye Yuan | 1 | 38 | 4.92 |
| Liangzhuo Xie | 2 | 0 | 0.34 |
| Yewen Zhu | 3 | 0 | 0.34 |
| Sheng Wang | 4 | 265 | 28.52 |
| Zhemin Zhuang | 5 | 5 | 4.48 |