In recent years, enormous efforts have been made to design image-processing algorithms to
enhance the spatial resolution of hyperspectral (HS) imagery. One of the most commonly …

Pansharpening aims at fusing a panchromatic image with a multispectral one, to generate
an image with the high spatial resolution of the former and the high spectral resolution of the …

The fusion of multispectral (MS) and hyperspectral (HS) images has recently been put in the
spotlight. The combination of high spatial resolution MS images with HS data showing a …

Semantic image inpainting is a challenging task where large missing regions have to be
filled based on the available visual data. Existing methods which extract information from …

Removal of noise from an image is an extensively studied problem in image processing.
Indeed, the recent advent of sophisticated and highly effective denoising algorithms has led …

Well-known compressed sensing (CS) is widely used in image acquisition and
reconstruction. However, accurately reconstructing images from measurements at low …

Hyperspectral remote sensing images (HSIs) usually have high spectral resolution and low
spatial resolution. Conversely, multispectral images (MSIs) usually have low spectral and …

Model-based reconstruction is a powerful framework for solving a variety of inverse
problems in imaging. In recent years, enormous progress has been made in the problem of …