Restoring a high-quality image from a noisy version poses a significant challenge in
computer vision, particularly in today's context where high-resolution and large-sized …

Variational regularization techniques are widely used to improve the quality of the super-
resolved image. However, the success of these methods depends on some sensitive …

When traditional super-resolution reconstruction methods are applied to infrared thermal
images, they often ignore the problem of poor image quality caused by the imaging …

Multi-image super-resolution (MISR) usually outperforms single-image super-resolution
(SISR) under a proper inter-image alignment by explicitly exploiting the inter-image …

In this paper, we propose a regularization technique for noisy-image super-resolution and
image denoising. Total variation (TV) regularization is adopted in many image processing …

Objective. Supervised deep learning for image super-resolution (SR) has limitations in
biomedical imaging due to the lack of large amounts of low-and high-resolution image pairs …

Microlens array (MLA) has been widely applied in optical imaging fields. However, the
existing MLA imaging system (MLAIS) often suffers the problems of low imaging resolutions …

Fluorescence microscopy is an important investigation tool of discoveries in the field of
biological sciences where the imaging phenomena are limited by the noise. This paper …

Image registration is a fundamental task for medical imaging. Resampling of the intensity
values is required during registration and better spatial resolution with finer and sharper …

Abstract Light-field (LF) super-resolution (SR) plays an essential role in alleviating the
current technology challenge in the acquisition of a 4D LF, which assembles both high …