This study provides an update of the polarimetric tools currently being used for optimum
information extraction from polarimetric synthetic aperture radar (SAR) images. The basics of …

Canada's successful space-based earth-observation (EO) radar program has earned
widespread and expanding user acceptance following the launch of RADARSAT-1 in 1995 …

The recent launches of three fully polarimetric synthetic aperture radar (PolSAR) satellites
have shown that polarimetric radar imaging can provide abundant data on the Earth's …

Aiming at improving the classification accuracy with limited numbers of labeled pixels in
polarimetric synthetic aperture radar (PolSAR) image classification task, this paper presents …

Polarimetric synthetic aperture radar (PolSAR) image segmentation is currently of great
importance in image processing for remote sensing applications. However, it is a …

Deep learning methods have been widely studied for Polarimetric synthetic aperture radar
(PolSAR) land cover classification. The scarcity of PolSAR labeled samples and the small …

This paper addresses estimation of the equivalent number of looks (ENL), an important
parameter in statistical modeling of multilook synthetic aperture radar (SAR) images. Two …

Remote sensing data, and radar data in particular, have become an essential tool for
environmental studies. Many airborne polarimetric sensors are currently operational, and …

Inspired by the popular deep learning architecture, deep stacking network (DSN), a specific
deep model for polarimetric synthetic aperture radar (POLSAR) image classification is …

The objective of this study is to evaluate the relationship between the response (σ°) of
airborne P-band Synthetic Aperture Radar (SAR) polarimetric data versus biomass values of …