This work is devoted to the mathematical analysis of an inverse source problem governed by
a time-fractional diffusion equation. The aims of this paper are to identify the source function …

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 …

This paper introduces a novel optimization procedure to reduce a mixture of Gaussian and
impulse noise from images. This framework is based on a non-convex PDE-constrained with …

To address the staircasing problem in deblurred images generated by a simple total
variation (TV) based model, one approach is to use the total fractional-order variation …

This work elaborated an improved method to multiframe super-resolution (SR), which
involves a nonlocal first-order regularization combined with a nonlocal p-Laplacian term …

Image denoising is an important topic in image processing. This paper proposes a novel
approach to speckle noise removal using a combination of nonlocal and local variable p …

This paper introduces an innovative bilevel optimization approach to elevate the deblurring
process. By integrating a weights variable nonlocal model with a spatially varying attached …

This research introduces an enhanced approach for multiframe super-resolution (SR) that
incorporates a bilevel optimization technique for learning the space variable weights …

Hybrid models are a class of powerful techniques that have earned considerable interest
recently, and this is because of their ability to handle complex and highly image-denoising …

In this paper, we propose a novel hybrid model combining local and nonlocal methods for
effective image denoising. The model utilizes variable exponents p (x) to achieve adaptive …