Image inpainting refers to the process of restoring missing or damaged areas in an image.
This field of research has been very active over recent years, boosted by numerous …

This paper proposes a technical review of exemplar-based inpainting approaches with a
particular focus on greedy methods. Several comparative and illustrative experiments are …

Many material and biological samples in scientific imaging are characterized by nonlocal
repeating structures. These are studied using scanning electron microscopy and electron …

Image super-resolution (SR) reconstruction is essentially an ill-posed problem, so it is
important to design an effective prior. For this purpose, we propose a novel image SR …

This paper introduces a novel examplar-based inpainting algorithm through investigating
the sparsity of natural image patches. Two novel concepts of sparsity at the patch level are …

Nonlocal texture similarity and local intensity smoothness are both essential for solving most
image inpainting problems. In this paper, we propose a novel image inpainting algorithm …

The search for efficient image denoising methods is still a valid challenge at the crossing of
functional analysis and statistics. In spite of the sophistication of the recently proposed …

In this paper, we first introduce a general approach for context-aware patch-based image
inpainting, where textural descriptors are used to guide and accelerate the search for well …

In this paper, we propose a patch-based image inpainting method using a low-rank Hankel
structured matrix completion approach. The proposed method exploits the annihilation …

Digital images are matrices of equally spaced pixels, each containing a photon count. This
photon count is a stochastic process due to the quantum nature of light. It follows that all …