Sum of Absolute Difference-based Rate-Distortion Optimization Cost Function for H.265/HEVC Intra-Mode Prediction

Naomi Z. Alariao, Kimberly P. Caguia, Patricia Anne J. Olaguer, Giljohn Andrew V. Sison, Jian Mae C. Valenton, Kanny Krizzy D. Serrano, Angelo R. dela Cruz
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Abstract

The emerging standard of High Efficiency Video Coding (HEVC) provides a 50% improved compression performance compared to its predecessor H.264/AVC at the expense of increasing its computational complexity which is due to a large number of modes involved in the decision process where it would increase encoding time and provide hardware limitations. In this paper, the reduction of intra-coding complexity is proposed by utilization of Rate-Distortion Optimization (RDO) in preselecting a mode with the best RD cost, among all 35 intra-modes. Two cost functions – Sum of Absolute Difference (SAD) and Sum of Absolute Transform Difference (SATD, available in the HEVC Test Model (HM) Reference Software, are determined by making encoder decisions. This paper compares the performance and complexity cost of SAD only for intra-mode, with SATD-based intra-mode by modifying the HM reference encoder through forced selection of the mentioned modes. Results show that SAD consistently produces the least encoding time among all modes, along with sensible values of bitrate. Furthermore, error concealment was introduced in decoding the video sequences with the use of IEEE 802.22 Standard which only allowed power gains resulting to packet error rates (PER) ranging from 1% to 30% for the analysis on the behavior of each video sequence in an environment where error is introduced.
基于绝对差分的H.265/HEVC模式内预测率失真优化代价函数和
与之前的H.264/AVC相比,新兴的高效视频编码(HEVC)标准提供了50%的压缩性能提升,但代价是增加了计算复杂度,这是由于决策过程中涉及大量模式,这会增加编码时间并提供硬件限制。本文提出了利用率失真优化(Rate-Distortion Optimization, RDO)在35种内模中预选RD成本最佳的模式来降低编码复杂度的方法。HEVC测试模型(HM)参考软件中提供的两个成本函数——绝对差和(SAD)和绝对变换差和(SATD),是通过编码器决策来确定的。本文比较了仅用于内模的SAD与通过强制选择上述模式修改HM参考编码器的基于sata的内模的性能和复杂性成本。结果表明,在所有模式中,SAD的编码时间最短,且比特率值合理。此外,在使用IEEE 802.22标准解码视频序列时引入了错误隐藏,该标准仅允许功率增益导致包错误率(PER)范围从1%到30%,用于分析每个视频序列在引入错误的环境中的行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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