Research in light field (LF) processing has heavily increased over the last decade. This is
largely driven by the desire to achieve the same level of immersion and navigational …

In recent years, visual sensors have been quickly improving, notably targeting richer
acquisitions of the light present in a visual scene. In this context, the so-called lenslet light …

In this paper, we present a compression method for light fields based on the Fourier
Disparity Layer representation. This light field representation consists in a set of layers that …

This paper addresses the problem of energy compaction of dense 4D light fields by
designing geometry-aware local graph-based transforms. Local graphs are constructed on …

In this paper we introduce a novel block-based regression strategy for image denoising
based on edge-aware Steered-Mixture-of-Experts (SMoE) models. SMoEs provide very …

Efficient storage and delivery of the light field (LF) information rely on high performance
compression. In this paper, we propose a high efficiency light field compression algorithm …

Steered-Mixtures-of-Experts (SMoE) models provide sparse, edge-aware representations,
applicable to many use-cases in image processing. This includes denoising, super …

In recent years, the research community has witnessed a growing interest in immersive
representations of the real world, such as light field. However, due to the increased volume …

This paper proposes a novel approach for lossless coding of light field (LF) images based
on a macro-pixel (MP) synthesis technique which synthesizes the entire LF image in one …

The Steered Mixture-of-Experts (SMoE) framework targets a sparse space-continuous
representation for images, videos, and light fields enabling processing tasks such as …