The demand for visual quality has been advanced by high display resolutions and frame rates. Nevertheless, these two issues have caused tremendous memory bandwidth in a video coding system. In this study, an efficient lossless embedded compression (EC) algorithm is proposed to save memory bandwidth, while keeping visual quality. The proposed lossless EC algorithm incorporates three core techniques: tree partition, half-pixel prediction and group-based binary coding. Tree partition classifies a 16×8 block into Trunk, Branch and Leaf. With tree partition, half-pixel prediction produces individual residues for Trunk, Branch and Leaf. Group-based binary coding converts theses residues to efficient codewords. The lossless compression ratio (CR) of the proposed EC is as high as 2.24 on average, saving memory bandwidth by 55.4%. This EC algorithm is implemented using CMOS 0.18μm technology. The maximum throughput can reach 6.4Gpixels/s, which can accommodate 3840 × 2160@60fps. The experiment results demonstrate that this study presents better hardware efficiency of 337Gpixels/J and 83.5Kpixels/s/gate.

中文翻译：

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用于高清视频编码系统的无损嵌入式压缩编码器的算法和 VLSI 架构设计

高显示分辨率和帧速率推动了对视觉质量的需求。然而，这两个问题在视频编码系统中造成了巨大的内存带宽。在这项研究中，提出了一种有效的无损嵌入式压缩 (EC) 算法来节省内存带宽，同时保持视觉质量。所提出的无损EC算法包含三种核心技术：树分割、半像素预测和基于组的二进制编码。树分区分类16×8分为树干、分支和叶子。通过树分区，半像素预测会为 Trunk、Branch 和 Leaf 生成单独的残差。基于组的二进制编码将这些残差转换为有效的代码字。提出的 EC 的无损压缩比 (CR) 平均高达 2.24，节省了 55.4% 的内存带宽。该 EC 算法使用 CMOS 0.18 实现μ米技术。最大吞吐量可达6.4Gpixels/s，可容纳3840×2160@60fps。实验结果表明，本研究提出了更好的硬件效率 337Gpixels/J 和 83.5千像素/秒/门。