In recent years, semantic segmentation with pixel-level classification has become one of the types research focus in field polarimetric synthetic aperture radar (PolSAR) image interpretation. Fully convolutional network (FCN) can achieve end-to-end segmentation, which provides a basic framework for subsequent improved networks. As classic FCN-based network, U-Net been applied to remote sensing ...

Recently, Polarimetric SAR (PolSAR) techniques have been much studied as hot research topics in the area of SAR. The objective of this paper is to assess the Principal component analysis (PCA) technique combining with multi-polarimetric SAR data for change detection. PCA proposed in this paper give an effective and quick way to achieve the difference map from the whole multi-temporal images, an...

In this Paper the potential of multi-temporal PolSARdata for soil surface roughness estimation is investigated. The study utilizes microwave backscatter collected from the Demmin test-site in the North-East Germany during the whole agri-phenological cycle in 2006 using quad-pol L-Band SLC E-SAR data. For ground truthing soil surface roughness were measured using photogrammetric imaging techniqu...

In this paper an unsupervised PolSAR data clustering algorithm utilizing the flexible polarimetric G distribution is proposed for the first time. This algorithm has been demonstrated in earlier contributions using other non-Gaussian distributions like K, G, and U distributions. The K and G distributions suffer from limited modeling capability due to the presence of only one shape parameter, whi...

The aim of this article was to investigate the potential polarimetric decomposition Chinese Gaofen-3 (GF-3) C-band fully synthetic aperture radar (PolSAR) data for Arctic sea ice classification during summer season. Five different approaches, including Cloude-Pottier (Cloude), Freeman three-component (Freeman3), using extended Bragg model (Freeman3X), Yamaguchi (Yamaguchi3), and nonnegative eig...

Synthetic Aperture Radar (SAR) data are affected by speckle noise, because of coherent integration of back scattered signals from different targets. For one-dimensional SAR data the speckle noise is already a solved problem, due to its multiplicative nature. SAR polarimetry is an extension to multidimensional data by the use of polarization wave diversity. Any speckle filter has to suppress the...

Superpixel generation of polarimetric synthetic aperture radar (PolSAR) images is widely used for intelligent interpretation due to its feasibility and efficiency. However, the initial superpixel size setting commonly neglected, empirical values are utilized. When prior information missing, a smaller value will increase computational burden, while higher may result in inferior boundary adherenc...