Name
Title | ||
|---|---|---|
Texture Parameter Estimation In Monopolarized Sar Imagery, For The Single Look Case, Using Extreme Value Theory |
Abstract | ||
|---|---|---|
Statistical modeling of Synthetic Aperture Radar (SAR) images is an important tool for image processing and interpretation, because it can contribute to a better understanding of the terrain electromagnetic scattering mechanisms. To that end, the G(I)(0) distribution is able to characterize a large number of targets. This distribution depends on three parameters: texture, scale, and the number of looks. The first has received special attention in the literature because it is closely related number of elementary backscatterers in the scene. In this paper we compare estimators for the texture parameter in the single look case. The single-look G(I)(0) law is a Pareto distribution whose tail index is related to the texture parameter, so we propose a tail index estimator. The estimators performance is analyzed in terms convergence, bias and mean squared error. Then we apply these estimators to actual data. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7729845 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
Image texture analysis, statistics, synthetic aperture radar images, speckle | Computer vision,Pareto distribution,Synthetic aperture radar,Computer science,Extreme value theory,Remote sensing,Image processing,Mean squared error,Artificial intelligence,Statistical model,Estimation theory,Estimator | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Debora Chan | 1 | 0 | 0.34 |
| Julia Cassetti | 2 | 0 | 0.68 |
| Alejandro C. Frery | 3 | 368 | 38.29 |