Dynamic Memory Model based Optimization of Scalar and Vector Quantizer Encoder

The rapid progress of computers and today''s heterogeneous computing environment means computation-intensive signal processing algorithms must be optimized in a machine-dependent fashion for best performance. Yet automatically re-targeting signal processing algorithms for a particular platform is a difficult problem. In this paper, using a dynamic memory model, the optimal computation-memory tradeoff is exploited to optimize the encoding time of scalar and vector quantizer. Experiments show marked improvements over existing techniques.