Polarization can provide information largely uncorrelated with the spectrum and intensity.
Therefore, polarimetric imaging (PI) techniques have significant advantages in many fields …

Unmanned ground vehicles (UGVs) have great potential in the application of both civilian
and military fields, and have become the focus of research in many countries. Environmental …

In this paper, to break the limit of the traditional linear models for synthetic aperture radar
(SAR) image despeckling, we propose a novel deep learning approach by learning a non …

Traditionally, clean reference images are needed to train the networks when applying the
deep learning techniques to tackle image denoising tasks. However, this idea is …

Estimating soil moisture based on synthetic aperture radar (SAR) data remains challenging
due to the influences of vegetation and surface roughness. Here we present an algorithm …

Synthetic aperture radar (SAR) images are inherently affected by speckle noise, for which
deep learning-based methods have shown good potential. However, the deep learning …

The fusion of multi-spectral and synthetic aperture radar (SAR) images could retain the
advantages of each data, hence benefiting accurate land cover classification. However …

Speckle is a granular deformity that frequently appears in images acquired through coherent
imaging sensors such as synthetic aperture radar (SAR). The existence of such noise in the …

Coherent imaging systems such as synthetic aperture radar (SAR) are subject to speckle,
the reduction of which is an active area of study. Methods based on deep convolutional …

Identifying the flooding risk hotspot is crucial for aiding a rapid response and prioritizes
mitigation efforts over large disaster impacted regions. While climate change is increasing …