Name
Abstract | ||
|---|---|---|
This paper introduces a generalisation of the conventional Maximum Likelihood (ML) texture tracking algorithm in the context of highly heterogeneous PolSAR clutter. The statistical criterion is defined in both uncorrelated and correlated texture cases. Some results on simulated data are computed and an application on temperate glaciers velocity estimation is processed. Finally, some additional improvements are performed: an adaptative sliding windows is set and a basic Bayes inference for flow model constraint is added. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/IGARSS.2010.5654061 | 2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM |
Keywords | Field | DocType |
synthetic aperture radar,computational modeling,image segmentation,clutter,maximum likelihood estimation,radar tracking,sliding window,maximum likelihood | Radar tracker,Synthetic aperture radar,Computer science,Remote sensing,Maximum likelihood,Image segmentation,Artificial intelligence,Bayes' theorem,Computer vision,Pattern recognition,Inference,Generalization,Clutter | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Olivier Harant | 1 | 0 | 0.34 |
| Lionel Bombrun | 2 | 150 | 20.59 |
| Gabriel Vasile | 3 | 145 | 18.88 |
| Laurent Ferro-Famil | 4 | 289 | 45.54 |
| Michel Gay | 5 | 54 | 6.77 |