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Memory Compaction and Power Optimization for Wavelet-Based Coders

  • V. Ferentinos
  • M. Milia
  • G. Lafruit
  • J. Bormans
  • F. Catthoor
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2799)

Abstract

A methodology for memory optimization in wavelet-based coders is presented. The dynamic memory requirements of the ASAP forward Wavelet Transform (WT) in three different output data grouping modes are studied: (a) independent output blocks with dyadically decreasing sizes; (b) zero-tree blocks and (c) independent equally-sized blocks. We propose an optimal approach of data clustering and calculation scheduling aiming at minimal memory requirements. This goal is reached using an appropriate subdivision of the filter inputs and it is verified with the assistance of an automatic design tool. The importance of the data dependencies between the different functional modules is shown to be dominant.

Keywords

Discrete Wavelet Transform Wavelet Transform Memory Requirement Data Dependency Memory Complexity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • V. Ferentinos
    • 1
  • M. Milia
    • 1
  • G. Lafruit
    • 1
  • J. Bormans
    • 1
  • F. Catthoor
    • 1
  1. 1.IMEC-DESICSLeuven-HeverleeBelgium

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