Lossless Intra Coding in HEVC with 3-tap Filters

This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC). A well-known previous pixel-by-pixel spatial prediction method uses only two neighboring pixels for prediction, based on the angular projection idea borrowed from block-based intra prediction in lossy coding. This paper explores a method which uses three neighboring pixels for prediction according to a two-dimensional correlation model, and the used neighbor pixels and prediction weights change depending on intra mode. To find the best prediction weights for each intra mode, a two-stage offline optimization algorithm is used and a number of implementation aspects are discussed to simplify the proposed prediction method. The proposed method is implemented in the HEVC reference software and experimental results show that the explored 3-tap filtering method can achieve an average 11.34% bitrate reduction over the default lossless intra coding in HEVC. The proposed method also decreases average decoding time by 12.7% while it increases average encoding time by 9.7%Comment: 10 pages, 7 figure

Piecewise mapping in HEVC lossless intra-prediction coding

The lossless intra-prediction coding modality of the High Efficiency Video Coding (HEVC) standard provides high coding performance while following frame-by-frame basis access to the coded data. This is of interest in many professional applications such as medical imaging, automotive vision and digital preservation in libraries and archives. Various improvements to lossless intra-prediction coding have been proposed recently, most of them based on sample-wise prediction using Differential Pulse Code Modulation (DPCM). Other recent proposals aim at further reducing the energy of intra-predicted residual blocks. However, the energy reduction achieved is frequently minimal due to the difficulty of correctly predicting the sign and magnitude of residual values. In this paper, we pursue a novel approach to this energy-reduction problem using piecewise mapping (pwm) functions. Specifically, we analyze the range of values in residual blocks and apply accordingly a pwm function to map specific residual values to unique lower values. We encode appropriate parameters associated with the pwm functions at the encoder, so that the corresponding inverse pwm functions at the decoder can map values back to the same residual values. These residual values are then used to reconstruct the original signal. This mapping is, therefore, reversible and introduces no losses. We evaluate the pwm functions on 4×4 residual blocks computed after DPCM-based prediction for lossless coding of a variety of camera-captured and screen content sequences. Evaluation results show that the pwm functions can attain maximum bit-rate reductions of 5.54% and 28.33% for screen content material compared to DPCM-based and block-wise intra-prediction, respectively. Compared to IntraBlock Copy, piecewise mapping can attain maximum bit-rate reductions of 11.48% for camera-captured material

DPCM-based edge prediction for lossless screen content coding in HEVC

Screen content sequences are ubiquitous type of video data in numerous multimedia applications like video conferencing, remote education, and cloud gaming. These sequences are characterized for depicting a mix of computer generated graphics, text, and camera-captured material. Such a mix poses several challenges, as the content usually depicts multiple strong discontinuities, which are hard to encode using current techniques. Differential pulse code modulation (DPCM)-based intra-prediction has shown to improve coding efficiency for these sequences. In this paper we propose sample-based edge and angular prediction (SEAP), a collection of DPCM-based intra-prediction modes to improve lossless coding of screen content. SEAP is aimed at accurately predicting regions depicting not only camera-captured material, but also those depicting strong edges. It incorporates modes that allow selecting the best predictor for each pixel individually based on the characteristics of the causal neighborhood of the target pixel. We incorporate SEAP into HEVC intra-prediction. Evaluation results on various screen content sequences show the advantages of SEAP over other DPCM-based approaches, with bit-rate reductions of up to 19.56% compared to standardized RDPCM. When used in conjunction with the coding tools of the screen content coding extensions, SEAP provides bit-rate reductions of up to 8.63% compared to RDPCM

Depth sequence coding with hierarchical partitioning and spatial-domain quantization

Depth coding in 3D-HEVC deforms object shapes due to block-level edge-approximation and lacks efficient techniques to exploit the statistical redundancy, due to the frame-level clustering tendency in depth data, for higher coding gain at near-lossless quality. This paper presents a standalone mono-view depth sequence coder, which preserves edges implicitly by limiting quantization to the spatial-domain and exploits the frame-level clustering tendency efficiently with a novel binary tree-based decomposition (BTBD) technique. The BTBD can exploit the statistical redundancy in frame-level syntax, motion components, and residuals efficiently with fewer block-level prediction/coding modes and simpler context modeling for context-adaptive arithmetic coding. Compared with the depth coder in 3D-HEVC, the proposed one has achieved significantly lower bitrate at lossless to near-lossless quality range for mono-view coding and rendered superior quality synthetic views from the depth maps, compressed at the same bitrate, and the corresponding texture frames. © 1991-2012 IEEE

Advanced methods and deep learning for video and satellite data compression

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