Name
Abstract | ||
|---|---|---|
The M estimator is a recently proposed image-quality index used to evaluate the despeckling operation in SAR (Synthetic Aperture Radar) data. It is used also to rank despeckling filters and to improve their design. As a difference with traditional image-quality estimators, it operates not on the filtered result but on a derived one, i.e., the ratio image. However, a deep statistical analysis of its properties remains open and, with it, the ability to use it as a test statistic. In this work, we focus on obtaining insights into its distribution as well as on exploring other remarkable statistical properties of this unassisted estimator. This study is performed through EDA (Exploratory Data Analysis) and the well-known ANOVA (ANalysis Of VAriance). We test our results on a set of simulated SAR data and provide guides to enrich the M estimator to extend its capabilities. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/rs11040385 | REMOTE SENSING |
Keywords | Field | DocType |
speckle,SAR,despeckling,image-quality index,M estimator,ANOVA | Computer vision,Remote sensing,Image quality,Artificial intelligence,Geology | Journal |
Volume | Issue | Citations |
11 | 4 | 1 |
PageRank | References | Authors |
0.36 | 25 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luis Gomez | 1 | 37 | 6.88 |
| Raydonal Ospina | 2 | 39 | 8.46 |
| Alejandro C. Frery | 3 | 368 | 38.29 |