Water body classification from high-resolution optical remote sensing (RS) images, aiming at
classifying whether each pixel of the image is water or not, has become a hot issue in the …

The increasing severity, duration, and frequency of destructive floods can be attributed to
shifts in climate, infrastructure, land use, and population demographics. Obtaining precise …

Worldwide and especially in less developed regions, process-based evaluations and/or
geomorphological information on large-scale rivers are still scarce. Such investigation …

Superpixel can maintain the boundary of the target and reduce the influence of speckle
noise, which has been widely applied to synthetic aperture radar (SAR) image target …

Synthetic aperture radar (SAR) satellite has been widely applied in real-time flood
monitoring as that they are not affected by extreme weather conditions. However, there is no …

Superpixel segmentation algorithms are predominently based on simple linear iterative
clustering (SLIC), and treat homogeneous and complex regions equally. This can lead to …

Machine learning and computer vision algorithms can provide a precise and automated
interpretation of medical videos. The segmentation of the left ventricle of echocardiography …

Most of the existing superpixel segmentation-based synthetic aperture radar (SAR) target
detection algorithms cannot keep the independence of small targets under complex …

We present a novel statistical model, the generalized-Gaussian–Rician (GG-Rician)
distribution, for the characterization of synthetic aperture radar (SAR) images. Since …

Flood map** plays a crucial role in effective disaster management, risk assessment, and
mitigation planning, given the widespread and destructive nature of floods. However, current …