Macroblock Feature Based Adaptive Propagate Partial SAD Architecture for HDTV Application

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  • Huang Yiqing
    Graduate School of Information, Production and Systems, Waseda University
  • Liu Qin
    Graduate School of Information, Production and Systems, Waseda University
  • Ikenaga Takeshi
    Graduate School of Information, Production and Systems, Waseda University

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Abstract

A macroblock (MB) feature based adaptive propagate partial SAD architecture is proposed in this paper. Firstly, by using edge detection operator, the homogeneous MB is detected before motion estimation and three hardware friendly subsampling patterns are adaptively selected for MB with different homogeneity. The proposed architecture uses four different processing elements to realize adaptive subsampling scheme. Secondly, in order to achieve data reuse and power reduction in memory part, the reference pixels in search window are reorganization into two memory groups, which output pixel data interactively for adaptive subsampling. Moreover, a compressor tree based circuit level optimization is included in our design to reduce hardware cost. Synthesized with TSMC 0.18um technology, averagely 10k gates hardware can be reduced for the whole IME engine based on our optimization. With 481k gates at 110.5MHz, an 720-p, 30-fps HDTV integer motion estimation engine is designed. Compared with previous work, our design can achieve 39.8% reduction in power consumption with only 3.44% increase in hardware.

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