Depth map compression via 3D region-based representation

In 3D video, view synthesis is used to create new virtual views between encoded camera views. Errors in the coding of the depth maps introduce geometry inconsistencies in synthesized views. In this paper, a new 3D plane representation of the scene is presented which improves the performance of current standard video codecs in the view synthesis domain. Two image segmentation algorithms are proposed for generating a color and depth segmentation. Using both partitions, depth maps are segmented into regions without sharp discontinuities without having to explicitly signal all depth edges. The resulting regions are represented using a planar model in the 3D world scene. This 3D representation allows an efficient encoding while preserving the 3D characteristics of the scene. The 3D planes open up the possibility to code multiview images with a unique representation.Postprint (author's final draft

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

Spatiotemporal adaptive quantization for the perceptual video coding of RGB 4:4:4 data

Due to the spectral sensitivity phenomenon of the Human Visual System (HVS), the color channels of raw RGB 4:4:4 sequences contain significant psychovisual redundancies; these redundancies can be perceptually quantized. The default quantization systems in the HEVC standard are known as Uniform Reconstruction Quantization (URQ) and Rate Distortion Optimized Quantization (RDOQ); URQ and RDOQ are not perceptually optimized for the coding of RGB 4:4:4 video data. In this paper, we propose a novel spatiotemporal perceptual quantization technique named SPAQ. With application for RGB 4:4:4 video data, SPAQ exploits HVS spectral sensitivity-related color masking in addition to spatial masking and temporal masking; SPAQ operates at the Coding Block (CB) level and the Prediction Unit (PU) level. The proposed technique perceptually adjusts the Quantization Step Size (QStep) at the CB level if high variance spatial data in G, B and R CBs is detected and also if high motion vector magnitudes in PUs are detected. Compared with anchor 1 (HEVC HM 16.17 RExt), SPAQ considerably reduces bitrates with a maximum reduction of approximately 80%. The Mean Opinion Score (MOS) in the subjective evaluations, in addition to the SSIM scores, show that SPAQ successfully achieves perceptually lossless compression compared with anchors