Name
Abstract | ||
|---|---|---|
In this paper, we propose a method towards unsupervised segmentation of synthetic aperture radar (SAR) image for segmentation of homogeneous regions. The SAR amplitude image is modeled by Rayleigh distribution. Moreover, in order to avoid geometric topology variations, the curve evolution is implemented via level sets. In addition, a new energy function is proposed, which is more objective and robust for the segmentation purpose. During the curve evolution, a convex factor is considered to guarantee the regularity of the region boundary. Finally, a novel termination criterion of the evolution of energy function is designed. And then, the effectiveness of our method is demonstrated on real SAR images. © 2013 Academy Publisher. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.4304/jsw.8.5.1168-1173 | JSW |
Keywords | Field | DocType |
active contours,level set,segmentation,synthetic aperture radar imagery | Scale-space segmentation,Synthetic aperture radar,Computer science,Segmentation-based object categorization,Level set,Image segmentation,Artificial intelligence,Rayleigh distribution,Computer vision,Segmentation,Algorithm,Inverse synthetic aperture radar,Machine learning | Journal |
Volume | Issue | Citations |
8 | 5 | 2 |
PageRank | References | Authors |
0.40 | 19 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiangqiang Peng | 1 | 10 | 1.64 |
| Long Zhao | 2 | 6 | 4.10 |