A Nonsmooth Graph-Based Approach to Light Field Super-Resolution

In this article we propose a new super-resolution algorithm tailored for light field cameras, which suffer by design from a limited spatial resolution. To do so, we cast the light field super-resolution problem into an optimization problem, where the particular structure of the light field data is captured by a nonsmooth graph-based regularizer, and all the light field views are super-resolved jointly. In our experiments, we show that the proposed method compares favorably to the state-of-the-art light field super-resolution algorithms in terms of PSNR and visual quality. In particular, the nonsmooth graph-based regularizer leads to sharper images while preserving fine details

Image Zoom Completion

We consider the problem of recovering a high-resolution image from a pair consisting of a complete low-resolution image and a high-resolution but incomplete one. We refer to this task as the image zoom completion (IZC) problem. After discussing possible contexts in which this setting may arise, we study three regularization strategies, giving full details concerning the numerical optimization of the corresponding energies, and discussing the benefits and shortcomings of each method. As the application that leads us to consider the IZC setting concerns images with strong textural content, we evaluate the performance of the proposed methods on a set of Brodatz textures, comparing the results we get with those obtained with two recent state-of-the-art single-image super-resolution algorithms

Transport optimal régularisé semi-déséquilibré pour la restauration d'images

In this paper we consider the use of a penalty based on optimal transport in order to regularize inverse problems in imaging. The proposed approach is formulated in a variational setting and aims at promoting images whose patch distribution is close either to the one learned by a generative model, or to available uncorrupted patches. With the aid of numerical illustrations, we argue in favor of adopting an asymmetric form of unbalanced transport. We then provide details concerning the computation and the differentiation of the proposed penalty. Finally, we detail the application of our approach to a particular super-resolution setting: the image zoom completion problem.Nous étudions dans cet article l'utilisation d'une pénalité basée sur le transport optimal afin de régulariser des problèmes inverses en traitement d'images. L'approche proposée est formulée dans un cadre variationnel et vise à favoriser des images dont les patchs ont une distribution proche de celle apprise par un modèle génératif, ou d'exemples non dégradés disponibles. À l'aide d'illustrations numériques, nous montrons la nécessité d'adopter une forme non symétrique de déséquilibre dans la formulation du transport optimal. Nous donnons ensuite les détails permettant de calculer et de différentier cette formulation. Enfin, nous détaillons son application à un problème particulier de super-résolution : la complétion de zoom