Test Zone Search Optimization Using Cuckoo Search Algorithm for VVC

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING International Journal of Multimedia Data Engineering & Management Pub Date : 2022-01-01 DOI:10.4018/ijmdem.314574
S. Acharjee, S. S. Chaudhuri
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引用次数: 2

Abstract

Motion vector approximation is an integral part of every video coding standard to reduce temporal correlation. Estimating motion necessitates a lot of computation. Several attempts were made to reduce the computation cost in exhaustive search of motion estimation. Test zone search was accepted as benchmark algorithm for fast motion estimation by the most recent video coding standard, versatile video coding. Quality and speed of test zone search completely depends on two parameters (i.e., sub sampling frequency of search space during raster scan and dimension of the search space). Cuckoo search, one of the popular nature-inspired optimization algorithms, is used to optimize the operational parameters of test zone search. The proposed optimization enhanced the speed up to 50% while maintaining or improving the Bjontegaard rate (BD-Rate) and Bjontegaard PSNR (BDSNR).
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基于布谷鸟搜索算法的VVC测试区域搜索优化
运动矢量近似是每个视频编码标准的一个组成部分,以减少时间相关性。估计运动需要大量的计算。为了在运动估计的穷举搜索中降低计算成本,进行了几次尝试。测试区域搜索被最新的视频编码标准通用视频编码接受为快速运动估计的基准算法。测试区搜索的质量和速度完全取决于两个参数(即光栅扫描期间搜索空间的子采样频率和搜索空间的维度)。杜鹃搜索是一种流行的自然优化算法,用于优化测试区搜索的操作参数。所提出的优化将速度提高了50%,同时保持或提高了Bjontegaard速率(BD rate)和Bjontegiard PSNR(BDSNR)。
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