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An efficient field programmable gate array based hardware architecture for efficient motion estimation with parallel implemented genetic algorithm

机译:一种基于现场可编程门阵列的基于硬件架构,具有通过并行实现的遗传算法的高效运动估计

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摘要

The main idea of this article is to propose a hardware design of block matching (BM) algorithm for an efficient motion estimation (ME) strategy in a field programmable gate array platform based on a parallel implemented genetic algorithm (GA). Easiness and the effectiveness of the BM algorithm while implementing have a major drawback of low quality and computationally cost expensive during the process of ME. Therefore, here in this article, we suggest GA based BM for a quick and cost-effective computation of motion vectors, without negotiating the quality factor. The ME carried out for various video sequences is implemented by using Xilinx ISE Design Suite 14.1. Delay, time, area, power, PSNR, MSE, SNR, SSIM, and NRMSE are the metrics used for analyzing the performance, and the simulation outcome shows that this parallel implemented BM architecture design shows an exotic improvement in time, quality and in utilization of power on estimating the motion than that of the conventional designs.
机译:本文的主要思想是提出基于并行实现的遗传算法(GA)的现场可编程门阵列平台中的高效运动估计(ME)策略的块匹配(BM)算法的硬件设计。 BM算法的容易性和有效性,同时实现在我的过程中具有低质量和计算成本的主要缺点。因此,在本文中,我们建议基于GA的BM,以便快速且经济有效地计算运动向量,而无需谈判质量因数。通过使用Xilinx ISE设计套件14.1来实现为各种视频序列进行的ME。延迟,时间,区域,电源,PSNR,MSE,SNR,SSIM和NRMSE是用于分析性能的指标,并且模拟结果表明,这种并行实施的BM架构设计显示了时代,质量和利用率的异国情调电源估计运动比传统设计的动力。

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