Title
Rayleigh Regression Model for Ground Type Detection in SAR Imagery
Abstract
This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of regressors and a link function. For the proposed model, we present: 1) parameter estimation; 2) large data record results; and 3) a detection technique. In this letter, we present closed-form expressions for the score vec...
Year
DOI
Venue
2019
10.1109/LGRS.2019.2904221
IEEE Geoscience and Remote Sensing Letters
Keywords
Field
DocType
Synthetic aperture radar,Radar polarimetry,Data models,Parameter estimation,Monte Carlo methods,Mathematical model,Detectors
Computer vision,Data modeling,Monte Carlo method,Synthetic aperture radar,Regression analysis,Algorithm,Gaussian,Artificial intelligence,Fisher information,Estimation theory,Mathematics,Estimator
Journal
Volume
Issue
ISSN
16
10
1545-598X
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Bruna G. Palm101.69
Fábio M. Bayer212612.89
Renato J. Cintra321826.82
Mats I. Pettersson412827.56
Renato Machado533.24