Abstract
Discrete Cosine Transform algorithm has emphasized the research attention for its ability to analyze application-based problems in signal and image processing like speech coding, image coding, filtering, cepstral analysis, topographic classification, progressive image transmission, data compression etc. This has major applications in pattern recognition and image processing. In this paper, a Cooley-Tukey approach has been proposed for computation of Discrete Cosine Transform and the necessary mathematical formulations have been developed for Star Graph connected multiprocessors. The signal flow graph of the algorithm has been designed for mapping onto the Star Graph. The modeling results are derived in terms of computation time, speedup and efficiency.
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