Name
Abstract | ||
|---|---|---|
This paper presents and discusses the use of a new feature for PolSAR imagery: the Generalized Statistical Complexity. This measure is able to capture the disorder of the data by means of the entropy, as well as its departure from a reference distribution. The latter component is obtained by measuring a stochastic distance between two models: the G0 and the Gamma laws. Preliminary results on the intensity components of AIRSAR image of San Francisco are encouraging. |
Year | Venue | Keywords |
|---|---|---|
2014 | ieee asia pacific conference on synthetic aperture radar | entropy,radar polarimetry,remote sensing by radar,stochastic processes,synthetic aperture radar,AIRSAR image intensity components,G0 model,PolSAR data,PolSAR imagery feature,San Francisco,data disorder capture,entropy,gamma law model,generalized statistical complexity,reference distribution departure,stochastic distance measurement |
Field | DocType | Volume |
Computer vision,Mathematical optimization,Algorithm,Artificial intelligence,Mathematics | Journal | abs/1402.1834 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| A.C. Frery | 1 | 132 | 8.86 |
| Eliana S. de Almeida | 2 | 0 | 0.34 |
| Osvaldo A. Rosso | 3 | 58 | 13.07 |