Name
Title | ||
|---|---|---|
Statistical Hypothesis Test For Maritime Pine Forest Sar Images Classification Based On The Geodesic Distance |
Abstract | ||
|---|---|---|
This paper introduces a new statistical hypothesis test for image classification based on the geodesic distance. We present how it can be used for the classification of texture image. The proposed method is then employed for the classification of Polarimetric Synthetic Aperture Radar images of maritime pine forests on both simulated data with the PolSARproSim software and real data acquired during the ONERA RAMSES campaign in 2004. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | Hypothesis test, SAR, geodesic distance, classification |
Field | DocType | ISSN |
Synthetic aperture radar,Computer science,Remote sensing,Software,Artificial intelligence,Contextual image classification,Statistical hypothesis testing,Computer vision,Pattern recognition,Inverse synthetic aperture radar,Parametric statistics,Image resolution,Geodesic | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ioana Ilea | 1 | 9 | 2.91 |
| Lionel Bombrun | 2 | 150 | 20.59 |
| Christian Germain | 3 | 113 | 18.95 |
| Isabelle Champion | 4 | 45 | 4.86 |
| Romulus Terebes | 5 | 49 | 8.42 |
| Monica Borda | 6 | 63 | 13.54 |