Style transfer describes the rendering of an image's semantic content as different artistic
styles. Recently, generative adversarial networks (GANs) have emerged as an effective …

This letter proposes a reconstruction-based single image super resolution method by using
joint regularization, where a group-residual-based regularization (GRR) and a ridge …

This paper presents a novel variational approach to imposing statistical constraints on the
output of both image generation (typically to perform texture synthesis) and image …

We consider in this paper the use of a penalty based on the theory of optimal transport (OT)
in order to regularize inverse problems in imaging. The proposed approach is formulated in …

We present a universal texture synthesis approach that incorporates a novel multiscale
texton broadcasting module in the StyleGAN-2 framework. The texton broadcasting module …

One of the main challenges of denoising approaches is preserving images details, like
textures and edges, while suppressing noise. The preservation of such details is essential to …

In this paper, we build on optimal transport (OT) theory to present a novel asymmetrically
unbalanced variant, the semi-unbalanced optimal transport (SUOT), specifically designed …

Existing image restoration methods mostly make full use of various image prior information.
However, they rarely exploit the potential of residual histograms, especially their role as …

We propose a 3-D material style transfer framework for reconstructing invisible (or faded)
appearance properties in complex natural materials. Our algorithm addresses the technical …

Recent developments in imaging techniques and computational analysis deeply modify the
way materials sciences. The materials image has moved from microscale resolution to true …