低功耗8×8视频压缩中运动估计的绝对差分引擎和

D. Manjunatha, G. Sainarayanan
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引用次数: 2

摘要

视频在电子和多媒体应用中越来越受欢迎,如视频电话、视频会议和通过互联网传输到移动电话的视频流,为了有效地使用视频,通常对视频进行压缩以获得低内存和快速传输的视频,然后再进行解压缩以供使用,因此视频压缩是目前非常活跃的研究课题,压缩是通过良好的运动估计(ME)来实现的。运动估计是视频压缩系统(VCS)中最耗电的部分。运动估计操作决定运动向量,给出运动的最佳方向,以及该运动向量的“适应度”。确定运动矢量最广泛使用的方法是绝对差和(SAD)。在本文中,我们实现了现有的和提出的8×8绝对差和。本文确定了用于低功耗应用的新型低功耗全加法单元,并将其用于所提出的绝对差分和算法中,使用ASIC流实现了设计,即使单元数从3933增加到4501,漏功率(LP)提高了28.74%,动态功率(DP)提高了12.201%,总功率提高了13.143%。
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Low power 8×8 Sum of Absolute Difference engine for Motion Estimation in video compression
Video is ever increasingly stimulating in electronics and multimedia applications such as video - telephony, video conferencing and video streaming to mobile phones via internet, in order to use effectively, the video is often compressed for low memory and fast transfer of video and then decompressed for use, so currently video compression a very active research topic, the compression is achieved through good Motion Estimation (ME). Motion Estimation is the power hungry block in the Video Compression System (VCS). The motion estimation operation determines the motion vectors, giving the best direction of the motion, and the "fitness" of that motion vector. The most widely used method to determine motion vectors is the Sum of Absolute Difference (SAD). In this paper we implemented the existing and the proposed 8×8 sum of absolute differences. Here the new low power full adder cell for low power applications is identified and is used in the proposed sum of absolute difference algorithm, the designs are implemented using ASIC flow, which results in 28.74% improvement in Leakage Power (LP) 12.201% improvement in Dynamic Power (DP) and 13.143% improvement in the total power even though the no of cells increased from 3933 to 4501.
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