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Fast and memory efficient text image compression with JBIG2.

Yan Ye1, Pamela Cosman

  • 1Video Group, Qualcomm Inc., San Diego, CA 92121, USA. yye@qualcomm.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 2, 2008
PubMed
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This study enhances JBIG2 text image compression by optimizing page striping and pattern matching, significantly reducing encoding time and memory usage. These methods also minimize substitution errors in lossy compression for better image quality.

Area of Science:

  • Computer Science
  • Image Processing
  • Data Compression

Background:

  • JBIG2 is a standard for lossless and lossy compression of bi-level images.
  • Encoding time, memory consumption, and substitution errors are key challenges in JBIG2 compression.
  • Page striping and pattern matching are computationally intensive processes in JBIG2 encoding.

Purpose of the Study:

  • To reduce encoding time and memory footprint for JBIG2 text image compression.
  • To minimize substitution errors in reconstructed images during lossy compression.
  • To optimize the trade-offs between compression speed, memory usage, and bit rate.

Main Methods:

  • Implementing page striping with dynamic dictionary updating procedures.
  • Developing an adaptive dictionary updating scheme.

Related Experiment Videos

  • Proposing three speedup techniques for pattern matching.
  • Introducing enhanced prescreening and feature monitored shape unifying for lossy compression.

    • Main Results:

    • Splitting images into two stripes reduced encoding time by 30% and memory by 40% with minimal coding loss.
    • Combined speedup techniques saved up to 75% of total encoding time with a 1.7% bit rate penalty.
    • Proposed methods significantly reduced substitution errors in reconstructed images.

    Conclusions:

    • Page striping and adaptive dictionary updates effectively balance encoding time, memory, and bit rate.
    • Speedup techniques for pattern matching offer substantial time savings with a minor bit rate increase.
    • Enhanced prescreening and shape unifying improve reconstructed image quality by reducing errors in lossy JBIG2 compression.