使用图形处理单元实现高效的运动估计和离散的等号变换
Shahrukh Agha1, Farmanullah Jan2, Haroon Ahmed Khan1
1Department of Electrical and Computer Engineering, COMSATS University Islamabad, Islamabad, Pakistan.
PloS one
|August 28, 2024
概括
图形处理单元 (GPU) 在HEVC视频编码中加速了计算密集的运动估计 (ME) 和2D离散等边变换 (2D-DCT). 这种GPU加速可实现高分辨率视频处理的实时性能.
科学领域:
- 计算机工程 计算机工程
- 视频压缩技术视频压缩技术
- 并行计算是一种平行计算.
背景情况:
- 高效视频编码 (HEVC) 标准涉及计算要求很高的运动估计 (ME) 和2D离散等边变换 (2D-DCT) 过程.
- 由于ME和2D-DCT的计算复杂性,HEVC的实时性能可能受到阻碍.
研究的目的:
- 在HEVC中使用图形处理单元 (GPU) 加快ME和2D-DCT任务.
- 分析GPU加速对实时应用的整体HEVC编码时间的影响.
主要方法:
- 探索四个平行水平 (框架,宏观块,搜索区域,SAD) 的ME.
- 实现多线程洛夫勒DCT算法用于2D-DCT计算.
- 对HEVC ME算法的比较分析,包括全搜索 (FS),测试区搜索 (TZS) 和高效层次钻石搜索 (EHDS).
主要成果:
- 在0.15秒内,GPU加速实现了ME处理25个高分辨率 (3840x2160) 的ME处理.
- 2D-DCT,图像重建和25的差异化在0.1秒内完成.
- 结合ME和2D-DCT任务在0.25秒内处理,为其他编码器组件留下了充足的时间.
结论:
- 在HEVC编码中,GPU部署显著提高了ME和2D-DCT的速度.
- 加速HEVC编码器适用于实时应用,因为处理时间缩短.
- 在基于GPU的视频处理加速中,不同级别的并行策略是有效的.
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