Speeding up motion estimation in modern video encoders using approximate metrics and SIMD processors

S. Pigeon, S. Coulombe
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引用次数: 7

Abstract

In the past, efforts have been devoted to the amelioration of motion estimation algorithms to speed up motion compensated video coding. Now, efforts are increasingly being directed at exploiting the underlying architecture, in particular, single instruction, multiple data (SIMD) instruction sets. The resilience of motion estimation algorithms to various error metrics allows us to propose new high performance approximate metrics based on the sum of absolute differences (SAD). These new approximate metrics are amenable to efficient branch-free SIMD implementations which yield impressive speed-ups, up to 11:1 in some cases, while sacrificing image quality for less than 0.1 dB on average.
利用近似度量和SIMD处理器加速现代视频编码器中的运动估计
在过去,人们一直致力于改进运动估计算法以加快运动补偿视频编码。现在,人们越来越多地致力于利用底层架构,特别是单指令多数据(SIMD)指令集。运动估计算法对各种误差度量的弹性使我们能够基于绝对差和(SAD)提出新的高性能近似度量。这些新的近似指标适用于高效的无分支SIMD实现,这些实现产生令人印象深刻的加速,在某些情况下高达11:1,同时牺牲图像质量,平均不到0.1 dB。
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