Exemplar-based texture synthesis consists in producing new synthetic images which have
the same perceptual characteristics as a given texture sample while exhibiting sufficient …

Texture synthesis has become an important topic in image processing, with many
fundamental applications in computer vision and image understanding. The purpose of this …

Designing realistic noise patterns from scratch is hard. To solve this problem, recent
contributions have proposed involved spectral analysis algorithms that enable procedural …

Inpainting consists in computing a plausible completion of missing parts of an image given
the available content. In the restricted framework of texture images, the image can be seen …

Super-resolution (SR) is an ill-posed inverse problem which consists in proposing high-
resolution images consistent with a given low-resolution one. While most SR algorithms are …

Super-Resolution (SR) is the problem that consists in reconstructing images that have been
degraded by a zoom-out operator. This is an ill-posed problem that does not have a unique …

A bilevel texture model is proposed, based on a local transform of a Gaussian random field.
The core of this method relies on the optimal transport of a continuous Gaussian distribution …

The anisotropic fractional Brownian field (AFBF) is a non-stationary Gaussian random field
which has been used for the modeling of textured images. In this paper, we address the …

Recent years have seen the rise of convolutional neural network techniques in exemplar-
based image synthesis. These methods often rely on the minimization of some variational …

Image inpainting consists in filling missing regions of an image by inferring from the
surrounding content. In the case of texture images, inpainting can be formulated in terms of …