Name
Title | ||
|---|---|---|
The Geodesic Distance between $\mathcal {G}_I^0$ Models and its Application to Region Discrimination. |
Abstract | ||
|---|---|---|
The GI0 distribution is able to characterize different regions in monopolarized SAR imagery. It is indexed by three parameters: the number of looks (which can be estimated in the whole image), a scale parameter, and a texture parameter. This paper presents a new proposal for feature extraction and region discrimination in SAR imagery, using the geodesic distance as a measure of dissimilarity betwe... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/JSTARS.2017.2647846 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Biological system modeling,Synthetic aperture radar,Data models,Computational modeling,Image edge detection,Level measurement,Numerical models | Computer vision,Level measurement,Data modeling,Numerical models,Pattern recognition,Synthetic aperture radar,Remote sensing,Feature extraction,Artificial intelligence,Geodesic,Scale parameter,Mathematics | Journal |
Volume | Issue | ISSN |
10 | 3 | 1939-1404 |
Citations | PageRank | References |
2 | 0.40 | 37 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Naranjo-Torres | 1 | 2 | 0.40 |
| Juliana Gambini | 2 | 41 | 5.57 |
| Alejandro C. Frery | 3 | 368 | 38.29 |