Signal processing algorithms and architectures can use dynamic reconfiguration to exploit variations in signal statistics with the objectives of improved performance and reduced power. Parameters provide a simple and formal way to characterize incremental changes to a computation and its computing mechanism. This paper develops a framework for dynamic parameterization and applies it to MPEG-4 motion estimation.A novel motion estimation architecture facilitates the dynamic variation of parameters to achieve power-compression tradeoffs. Our work shows that parameter variation in motion estimation helps achieve power reduction by an order of magnitude, trading off higher ii

For motion estimation (ME) and discrete cosine transform (DCT)

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