Overview of MV-HEVC prediction structures for light field video

Light field video is a promising technology for delivering the required six-degrees-of-freedom for natural content in virtual reality. Already existing multi-view coding (MVC) and multi-view plus depth (MVD) formats, such as MV-HEVC and 3D-HEVC, are the most conventional light field video coding solutions since they can compress video sequences captured simultaneously from multiple camera angles. 3D-HEVC treats a single view as a video sequence and the other sub-aperture views as gray-scale disparity (depth) maps. On the other hand, MV-HEVC treats each view as a separate video sequence, which allows the use of motion compensated algorithms similar to HEVC. While MV-HEVC and 3D-HEVC provide similar results, MV-HEVC does not require any disparity maps to be readily available, and it has a more straightforward implementation since it only uses syntax elements rather than additional prediction tools for inter-view prediction. However, there are many degrees of freedom in choosing an appropriate structure and it is currently still unknown which one is optimal for a given set of application requirements. In this work, various prediction structures for MV-HEVC are implemented and tested. The findings reveal the trade-off between compression gains, distortion and random access capabilities in MVHEVC light field video coding. The results give an overview of the most optimal solutions developed in the context of this work, and prediction structure algorithms proposed in state-of-the-art literature. This overview provides a useful benchmark for future development of light field video coding solutions

HEVC-based 3D holoscopic video coding using self-similarity compensated prediction

Holoscopic imaging, also known as integral, light field, and plenoptic imaging, is an appealing technology for glassless 3D video systems, which has recently emerged as a prospective candidate for future image and video applications, such as 3D television. However, to successfully introduce 3D holoscopic video applications into the market, adequate coding tools that can efficiently handle 3D holoscopic video are necessary. In this context, this paper discusses the requirements and challenges for 3D holoscopic video coding, and presents an efficient 3D holoscopic coding scheme based on High Efficiency Video Coding (HEVC). The proposed 3D holoscopic codec makes use of the self-similarity (SS) compensated prediction concept to efficiently explore the inherent correlation of the 3D holoscopic content in Intra- and Inter-coded frames, as well as a novel vector prediction scheme to take advantage of the peculiar characteristics of the SS prediction data. Extensive experiments were conducted, and have shown that the proposed solution is able to outperform HEVC as well as other coding solutions proposed in the literature. Moreover, a consistently better performance is also observed for a set of different quality metrics proposed in the literature for 3D holoscopic content, as well as for the visual quality of views synthesized from decompressed 3D holoscopic content.info:eu-repo/semantics/submittedVersio

Fast Motion Estimation Algorithms for Block-Based Video Coding Encoders

The objective of my research is reducing the complexity of video coding standards in real-time scalable and multi-view applications