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This paper proposes a deep learning method for intra prediction. Different from traditional methods utilizing some fixed rules, we propose using a fully connected network to learn an end-to-end mapping from neighboring reconstructed pixels to the current block. In the proposed method, the network is fed by multiple reference lines. Compared with traditional single line-based methods, more contextual information of the current block is utilized. For this reason, the proposed network has the potential to generate better prediction. In addition, the proposed network has good generalization ability on different bitrate settings. The model trained from a specified bitrate setting also works well on other bitrate settings. Experimental results demonstrate the effectiveness of the proposed method. When compared with high efficiency video coding reference software HM-16.9, our network can achieve an average of 3.4% bitrate saving. In particular, the average result of 4K sequences is 4.5% bitrate saving, where the maximum one is 7.4%. [ABSTRACT FROM AUTHOR]

Screen content coding plays an important role in many applications. Conventional reference picture management (RPM) strategies developed for natural content may not work well for screen content. This is because many regions in screen content remain static for a long time, causing a lot of repetitive contents to stay in the decoded picture buffer. The repetitive contents are not conducive to inter prediction, but still occupy valuable memory. This paper proposes a diversity-based RPM scheme for screen content coding. The concept of diversity is introduced for the reference picture set (RPS) to help formulate the RPM problem. By maximizing the diversity of RPS, more potentially better predictions are provided. Better compression performance can then be achieved. Meanwhile, the proposed scheme is nonnormative and compatible with existing video coding standards, such as High Efficiency Video Coding. The experimental results show that, for low delay screen content coding, the bit saving of the proposed scheme is 4.9% on average and up to 13.7%, without increasing encoding time. [ABSTRACT FROM AUTHOR]

A screen content coding (SCC) extension to High Efficiency Video Coding (HEVC) is currently under development by the Joint Collaborative Team on Video Coding, which is a joint effort from the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group. The main goal of the HEVC-SCC standardization effort is to enable significantly improved compression performance for videos containing a substantial amount of still or moving rendered graphics, text, and animation rather than, or in addition to, camera-captured content. This paper provides an overview of the technical features and characteristics of the current HEVC-SCC test model and related coding tools, including intra-block copy, palette mode, adaptive color transform, and adaptive motion vector resolution. The performance of the SCC extension is compared against existing standards in terms of bitrate savings at equal distortion. [ABSTRACT FROM PUBLISHER]

The Range Extensions (RExt) of the High Efficiency Video Coding (HEVC) standard have recently been approved by both ITU-T and ISO/IEC. This set of extensions targets video coding applications in areas including content acquisition, postproduction, contribution, distribution, archiving, medical imaging, still imaging, and screen content. In addition to the functionality of HEVC Version 1, RExt provide support for monochrome, 4:2:2, and 4:4:4 chroma sampling formats as well as increased sample bit depths beyond 10 bits per sample. This extended functionality includes new coding tools with a view to provide additional coding efficiency, greater flexibility, and throughput at high bit depths/rates. Improved lossless, near-lossless, and very high bit-rate coding is also a part of the RExt scope. This paper presents the technical aspects of HEVC RExt, including a discussion of RExt profiles, tools, applications, and provides experimental results for a performance comparison with previous relevant coding technology. When compared with the High 4:4:4 Predictive Profile of H.264/Advanced Video Coding (AVC), the corresponding HEVC 4:4:4 RExt profile provides up to $\sim 25$ %, $\sim 32$ %, and $\sim 36$ % average bit-rate reduction at the same PSNR quality level for intra, random access, and low delay configurations, respectively. [ABSTRACT FROM PUBLISHER]

Motion compensation with multiple reference pictures has been widely used during the development of the emerging High Efficiency Video Coding (HEVC) standard, which greatly helps to improve the coding efficiency. Usually, a heuristic strategy is exploited to use the nearest reconstructed pictures as references. However, such a strategy may not be efficient on all occasions, especially when different content characteristics and coding settings are considered. In this paper, we investigate how to manage reference pictures so as to achieve better rate-distortion performance under the memory constraint of the decoded picture buffer at the decoder. We formulate the reference picture management as an optimization problem and approximate its optimal solution. Moreover, we explore how to adjust quality for each picture according to the reference structure to further improve coding efficiency. For some coding cases, where a complicated encoder optimization is unaffordable, we also develop fast algorithms to get the most benefit from reference picture selection. Among them, one strategy has been adopted by the HEVC software and common test conditions to generate the anchor. Experimental results show that the proposed full search algorithm and fast search algorithms achieve significant bitrate reduction. [ABSTRACT FROM PUBLISHER]

Computers are developing along with a new trend from the dual-core and quad-core processors to ones with tens or even hundreds of cores. Multimedia, as one of the most important applications in computers, has an urgent need to design parallel coding algorithms for compression. Taking intraframe/image coding as a start point, this paper proposes a pure line-by-line coding scheme (LBLC) to meet the need. In LBLC, an input image is processed line by line sequentially, and each line is divided into small fixed-length segments. The compression of all segments from prediction to entropy coding is completely independent and concurrent at many cores. Results on a general-purpose computer show that our scheme can get a 13.9 times speedup with 15 cores at the encoder and a 10.3 times speedup at the decoder. Ideally, such near-linear speeding relation with the number of cores can be kept for more than 100 cores. In addition to the high parallelism, the proposed scheme can perform comparatively or even better than the H.264 high profile above middle bit rates. At near-lossless coding, it outperforms H.264 more than 10 dB. At lossless coding, up to 14% bit-rate reduction is observed compared with H.264 lossless coding at the high 4:4:4 profile. [ABSTRACT FROM PUBLISHER]