Steered Mixture-of-Experts (SMoE) is a novel framework for representing multidimensional image modalities. In this paper, we propose a coding methodology for SMoE models that is readily extendable to any dimensional SMoE model, thus representing any image modality of any dimension. We evaluate the coding performance of SMoE models of light field video, a 5D image modality, i.e. time, two angular, and two spatial dimensions. The coding consists of the exploiting the redundancy between the parameters of SMoE models, i.e. a set of multivariate Gaussian distributions. We compare the performance of three multi-view HEVC (MV-HEVC) configurations that differ in terms of random access. Each subaperture view from the light field video is interpreted as a single view in MV-HEVC. Experiments validate that excellent coding performance compared to MV-HEVC for low- to midrange bitrates in terms of PSNR and SSIM with bitrate savings up to 75%.

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Vasileios Avramelos, Ignace Saenen, Ruben Verhack, Glenn Van Wallendael, Peter Lambert, and Thomas Sikora, "Steered mixture-of-experts for light field video coding," Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107520B (Presented at SPIE Optical Engineering + Applications: August 20, 2018; Published: 17 September 2018); https://doi.org/10.1117/12.2320563.