Remote sensing image super-resolution (SR) refers to a technique improving the spatial
resolution, which in turn benefits to the subsequent image interpretation, eg, target …

Super-resolution imaging has, for more than seventy years, gradually evolved to produce
advanced methods for enhancing the resolution of images beyond the diffraction limits …

Synthetic aperture radar (SAR) is an important means for target surveillance through
reconstructing the microwave image of the observation area. However, under the condition …

Objective: To introduce an MRI in-plane resolution enhancement method that estimates
High-Resolution (HR) MRIs from Low-Resolution (LR) MRIs. Method & Materials: Previous …

This paper introduces a sparse scene reconstruction algorithm for automobile frequency-
modulated continuous-wave synthetic aperture radar (FMCW SAR) through scaled …

Single image super-resolution (SISR) is a challenging work, which aims to recover the
missing information in an observed low-resolution (LR) image and generate the …

Super resolution (SR) is an attractive issue in image processing. In the synthetic aperture
radar (SAR) image, speckle noise is a crucial problem that is multiplicative. Therefore …

As an active microwave coherent imaging technology, synthetic aperture radar (SAR)
images suffer from severe speckle noise and low-resolution problems due to the limitations …

Deep learning methods, in particular, trained convolutional neural networks (CNNs) have
recently been shown to produce compelling results for single image super-resolution (SR) …

Due to a unique imaging mechanism, Synthetic Aperture Radar (SAR) images typically
exhibit degradation phenomena. To enhance image quality and support real-time on-board …