Image super-resolution (SR) is one of the vital image processing methods that improve the
resolution of an image in the field of computer vision. In the last two decades, significant …

Super-resolution (SR) technique reconstructs a higher-resolution image or sequence from
the observed LR images. As SR has been developed for more than three decades, both …

Modern handheld devices can acquire burst image sequence in a quick succession.
However, the individual acquired frames suffer from multiple degradations and are …

While single-image super-resolution (SISR) has attracted substantial interest in recent years,
the proposed approaches are limited to learning image priors in order to add high frequency …

Compared to DSLR cameras, smartphone cameras have smaller sensors, which limits their
spatial resolution; smaller apertures, which limits their light gathering ability; and smaller …

Super-resolution, the process of obtaining one or more high-resolution images from one or
more low-resolution observations, has been a very attractive research topic over the last two …

Video super-resolution (SR) aims at generating a sequence of high-resolution (HR) frames
with plausible and temporally consistent details from their low-resolution (LR) counterparts …

Remote sensing satellite sensors feature a tradeoff between the spatial, temporal, and
spectral resolutions. In this paper, we propose an integrated framework for the spatio …

Although multiframe super resolution has been extensively studied in past decades, super
resolving real-world video sequences still remains challenging. In existing systems, either …

Background and objective With the high-resolution (HR) requirements of medical images in
clinical practice, super-resolution (SR) reconstruction algorithms based on low-resolution …