Share Email Print
cover

Optical Engineering

Fractal image compression based on intrablock variance distribution and vector quantization
Author(s): Shin-Si Chen; Chang-Biau Yang; Kuo-Si Huang
Format Member Price Non-Member Price
PDF $20.00 $25.00

Paper Abstract

In the encoding phase of fractal image compression, most of the time is taken in finding the closest match between each range block and a large pool of domain blocks. We use the intrablock variance distributions of domain blocks to reduce the search space. For finding a close match, we need search only the domain blocks whose maximal intrablock variance quadrants are at the same corner as the range block. Thus, we reduce the number of transforms applied on each domain block from eight to two. We also adopt the longest-distance-first vector quantization scheme to divide the large pool of domain blocks into clusters. Thus, the number of domain blocks to be searched is also reduced. The experimental results show that our algorithm can reduce encoding time with only slight loss of quality.

Paper Details

Date Published: 1 November 2002
PDF: 7 pages
Opt. Eng. 41(11) doi: 10.1117/1.1510743
Published in: Optical Engineering Volume 41, Issue 11
Show Author Affiliations
Shin-Si Chen, National Sun Yat-sen Univ. (Taiwan)
Chang-Biau Yang, National Sun Yat-sen Univ. (Taiwan)
Kuo-Si Huang, National Sun Yat-sen Univ. (Taiwan)


© SPIE. Terms of Use
Back to Top