A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is
In this paper we develop a supervised classification approach for medium and high resolution multichannel synthetic aperture radar (SAR) amplitude images. The proposed technique combines finite mixture modeling for probability density function estimation, copulas for multivariate distribution modeling and a Markov random field (MRF) approach to Bayesian classification. The novelty of this research is in introduction of copulas to classification of D-channel SAR, with D 3, within the mainframedoi:10.1063/1.3573633 fatcat:vkcxqaldozcdxafdvjyo6dhbka