Evolutionary Multiresolution Matching Pursuit and its relations with the Human Visual System

This paper proposes a multiresolution Matching Pursuit decomposition of natural images. Matching Pursuit is a greedy algorithm that decomposes any signal into a linear expansion of waveforms taken from a redundant dictionary, by iteratively picking the waveform that best matches the input signal. Since the computational cost rapidly grows with the size of the signal, we propose a multiresolution strategy that, together with a dictionary training, significantly reduces the encoding complexity while still providing an efficient representation. Such a decomposition is perceptually very effective at low bit rate coding, thanks to similiarities with the Human Visual System information processing.

    Keywords: LTS2 ; LTS4




    • EPFL-REPORT-86782

    Record created on 2006-06-14, modified on 2017-05-10

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