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Related Experiment Videos

An algorithm for compression of bilevel images.

M D Reavy1, C G Boncelet

  • 1Dept. of Electr. and Comput. Eng., Delaware Univ., Newark, DE 19716, USA. mreavy@wgate.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|February 6, 2008
PubMed
Summary

Block Arithmetic Coding for Image Compression (BACIC) offers a new lossless bilevel image compression method. It achieves compression ratios comparable to JBIG, presenting a viable alternative for efficient image data encoding.

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Area of Science:

  • Computer Science
  • Image Processing
  • Data Compression

Background:

  • The Joint Bilevel Image Experts Group (JBIG) is the current standard for lossless bilevel image compression.
  • JBIG utilizes a patented arithmetic coder (IBM QM-coder) and predetermined probability tables.
  • JBIG has not been commercially implemented, with its predecessor, Group 3 fax (G3), still in use.

Purpose of the Study:

  • Introduce Block Arithmetic Coding for Image Compression (BACIC) as a novel algorithm for lossless bilevel image compression.
  • Present BACIC as a potential replacement for existing standards like JBIG and G3.
  • Demonstrate BACIC's efficiency and comparable performance to established compression methods.

Main Methods:

  • BACIC employs a Block Arithmetic Coder (BAC), a variable-to-fixed arithmetic coder.

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  • Probability estimates are adaptively modeled using a 12-bit context of previous pixel values.
  • The 12-bit context indexes a probability table to compute p(1), essential for codeword generation.

    • Main Results:

    • BACIC achieves compression ratios comparable to JBIG across various image types.
    • For CCITT test images, BACIC yielded a 19.0 compression ratio (JBIG: 19.6, G3: 7.7).
    • For business documents, BACIC achieved 16.0 (JBIG: 16.0, G3: 6.74), and for halftone images, 3.07 (JBIG: 2.75, G3: 0.50).

    Conclusions:

    • BACIC is a competitive alternative to JBIG and G3 for lossless bilevel image compression.
    • The algorithm demonstrates strong performance, achieving compression ratios on par with the current standard.
    • BACIC's adaptive probability estimation and simple coder design offer efficiency and ease of implementation.