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Hierarchical dynamic range coding of wavelet subbands for fast and efficient image decompression.

Yushin Cho1, William A Pearlman

  • 1Sony Electronics, Inc., San Jose, CA 95112, USA. cho.yushin@gmail.com

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|August 11, 2007
PubMed
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A new image coding algorithm, Progressive Resolution Coding (PROGRES), offers significantly faster decoding speeds than SPIHT. PROGRES achieves this by predicting wavelet subband ranges, maintaining coding efficiency without quality scalability.

Area of Science:

  • Digital image processing
  • Wavelet transforms
  • Image compression

Background:

  • Scalable image coding is crucial for efficient transmission and storage.
  • Existing methods like SPIHT (Set Partitioning In Hierarchical Trees) offer good compression but can be computationally intensive for decoding.
  • There is a need for faster decoding algorithms without sacrificing compression efficiency.

Purpose of the Study:

  • To propose a novel image coding algorithm, Progressive Resolution Coding (PROGRES), optimized for high-speed resolution scalable decoding.
  • To investigate the performance of PROGRES in terms of decoding speed and coding efficiency compared to existing methods.
  • To explore the extensibility of PROGRES for random access decoding.

Main Methods:

  • PROGRES algorithm designed based on prediction of decaying dynamic ranges of wavelet subbands.

Related Experiment Videos

  • Bypasses bit-plane coding and complex list processing found in SPIHT.
  • Algorithm implemented and tested for both 2-D and 3-D wavelet subbands.

    • Main Results:

    • PROGRES decoding speeds are 4x faster for 2-D and 9x faster for 3-D compared to uncoded SPIHT, with similar decoded quality.
    • Coding efficiency is comparable to uncoded SPIHT, with identical bitstreams in the lossless case.
    • Demonstrates suitability for very large scale image encoding and decoding due to higher speed gains on larger images.

    Conclusions:

    • PROGRES provides a significant speed improvement for scalable image decoding.
    • The algorithm maintains high coding efficiency and is easily extensible for random access.
    • PROGRES is a viable alternative for applications requiring fast decoding of wavelet-based image compression.