基于降位的最优运动估计及其低功耗VLSI实现

S. Agha, Farmanullah Jan, Dilshad Sabir, Khurram Saleem, Usman Ali Gulzari, Atif Shakeel
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引用次数: 1

摘要

全搜索运动估计(M.E.)过程计算量大,功耗大,可能不适合电池供电的实时应用。在这项工作中,不同的M.E.算法被提出。算法1至算法3有利于低功耗和高吞吐量VLSI实现,同时保持最佳质量水平。针对这三种算法,给出了三种VLSI架构。理论上,架构1减少了内存中的像素访问,从而减少了23%的功耗。架构2减少了48%的像素访问,架构3减少了52%的像素访问。最后,我们提出了一种次优快速M.E.算法,该算法是对钻石搜索算法的改进形式,与标准钻石搜索M.E.算法相比,具有更低的复杂度和更高的质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal motion estimation using reduced bits and its low power VLSI implementation
Full search Motion Estimation (M.E.) process is computationally intensive and power consuming, which might be unsuitable for battery powered real time applications. In this work, different M.E. algorithms are being presented. Algorithms 1 to 3 are beneficial for low power and high throughput VLSI implementation while keeping the quality at optimum level. Three VLSI architectures are presented corresponding to the three algorithms. Theoretically, Architecture 1 reduces the pixel accesses from memory and hence power consumption by 23%. Architecture 2 reduces the pixel accesses by 48% and Architecture 3 reduces pixel accesses by 52%. Finally we present a suboptimal fast M.E. algorithm which is a modified form of Diamond Search algorithm, has less complexity and improved quality as compared to standard diamond search M.E. algorithm.
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