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Related Experiment Videos

Source coding with a permutation-based reversible memory-binding transform for data compression in categorical data

B G Talbot1, L M Talbot

  • 1TASC Inc., Chantilly, VA 20151, USA. bgtalbot@tasc.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 16, 2008
PubMed
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A novel memory-binding transform (MBT) effectively encodes data by permuting signal alphabets. This reversible algorithm enhances compression for various data types when paired with Huffman coding.

Area of Science:

  • Information Theory
  • Data Compression
  • Signal Processing

Background:

  • Data compression is crucial for efficient storage and transmission.
  • Existing methods may have limitations with diverse data types.

Purpose of the Study:

  • To develop a general-purpose reversible data transformation technique.
  • To improve compression efficiency for ordered and categorical data.

Main Methods:

  • Introduced a memory-binding transform (MBT) using permutation techniques.
  • Bound memory information to a transformed signal alphabet.
  • Evaluated MBT with a Huffman coder.

Main Results:

  • The MBT algorithm demonstrated effective performance.

Related Experiment Videos

  • Successful application to ordered sources like pixel intensities.
  • Successful application to categorical sources like vector quantized codebook indices.

    • Conclusions:

    • The developed MBT is a versatile tool for data compression.
    • MBT offers improved compression for a wide range of data sources.
    • The combination of MBT and Huffman coding provides significant benefits.