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Proceedings Paper

Fast methods for fractal image encoding
Author(s): Gregory Caso; Pere Obrador; C.-C. Jay Kuo
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Paper Abstract

Fractal image compression is a relatively new and very promising technique for still image compression. However, it is not widely applied due to its very time consuming encoding procedure. In this research, we focus on speeding up this procedure by introducing three schemes: dimensionality reduction, energy-based classification, and tree search. We have developed an algorithm that combines these three schemes together and achieves a speed-up factor of 175 at the expense of only 0.6 dB degradation in PSNR relative to the unmodified exhaustive search for a typical image encoded with 0.44 bpp.

Paper Details

Date Published: 21 April 1995
PDF: 12 pages
Proc. SPIE 2501, Visual Communications and Image Processing '95, (21 April 1995); doi: 10.1117/12.206767
Show Author Affiliations
Gregory Caso, Univ. of Southern California (United States)
Pere Obrador, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 2501:
Visual Communications and Image Processing '95
Lance T. Wu, Editor(s)

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