Assessing the visual quality of super-resolution images (SRIs) is crucial for advancing
algorithm development, but it remains an unsolved problem. In this paper, we present a …

Lightweight convolutional neural networks for Single Image Super-Resolution (SISR) have
exhibited remarkable performance improvements in recent years. These models achieve …

Image downscaling is one of the widely used operations in image processing and computer
graphics. It was recently demonstrated in the literature that kernel-based convolutional filters …

Image resizing (IR) has a crucial role in remote sensing (RS), since an image's level of detail
depends on the spatial resolution of the acquisition sensor; its design limitations; and other …

Video super-resolution (SR) has important real world applications such as enhancing
viewing experiences of legacy low-resolution videos on high resolution display devices …

Image interpolation algorithms pervade many modern image processing and analysis
applications. However, when their weighting schemes inefficiently generate very unrealistic …

Although high resolution (HR) depth images are required in many applications such as
virtual reality and autonomous navigation, their resolution and quality generated by …

Spatial color algorithms (SCAs) are algorithms grounded in the retinex theory of color
sensation that, mimicking the human visual system, perform image enhancement based on …

The paper deals with the numerical solution of Cauchy Singular Integral Equations based on
some non standard polynomial quasi–projection of de la Vallée Poussin type. Such kind of …

In this paper, we propose new three-dimensional (3D) visualization of objects at long
distance under photon-starved conditions. In conventional three-dimensional image …