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

Ultra high definition video decoding with motion JPEG XR using the GPU

Many applications require real-time decoding of highresolution video pictures, for example, quick editing of video sequences in video editing applications. To increase decoding speed, parallelism can be exploited, yet, block-based image and video coding standards are difficult to decode in parallel because of the high number of dependencies between blocks. This paper investigates the parallel decoding capabilities of the new JPEG XR image coding standard for use on the massively-parallel architecture of the GPU. The potential of parallelism of the hierarchical frequency coding scheme used in the standard is addressed and a parallel decoding scheme is described suitable for real-time decoding of Ultra High Definition (4320p) Motion JPEG XR video sequences. Our results show a decoding speed of up to 46 frames per second for Ultra High Definition (4320p) sequences with high-dynamic range (32-bit/ 4: 2: 0) luma and chroma components