Polarimetric features are essential to polarimetric synthetic aperture radar (PolSAR) image
classification for their better physical understanding of terrain targets. The designed …

Polarimetric features extracted from polarimetric synthetic aperture radar (PolSAR) images
contain abundant back-scattering information about objects. Utilizing this information for …

Image classification is a critical and important application in PolSAR image interpretation.
Finding a feature extraction method, which can effectively describe the characteristics of the …

The availability of polarimetric synthetic aperture radar (PolSAR) images has increased, and
consequently, the classification of such images has received immense attention. Among …

Polarimetric synthetic aperture radar (PolSAR) image classification has been investigated
vigorously in various remote sensing applications. However, it is still a challenging task …

A novel polarimetric synthetic aperture radar (POL-SAR) image classification approach is
proposed in this paper by exploiting coherency matrix eigenvalues for polarimetric …

The approaches for analyzing the polarimetric scattering matrix of polarimetric synthetic
aperture radar (PolSAR) data have always been the focus of PolSAR image classification …

The speckle effect embedded in polarimetric synthetic aperture radar (PolSAR) data
damages the performance of PolSAR image classification greatly. To alleviate this issue, a …

The phase difference, amplitude product, and amplitude ratio between two polarizations are
important discriminators for terrain classification, which derives a significant statistical …

This letter presents a feature weighting method for polarimetric synthetic aperture radar
(PolSAR) image classification. Appropriate feature weighting is essential for obtaining …