A nonlinear model for fractal image coding

After a very promising start, progress in fractal image coding has been relatively slow recently. Most improvements have been concentrating on better adaptive coding algorithms and on search strategies to reduce the encoding time. Very little has been-done to challenge the linear model of the fracta...

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Bibliographic Details
Published in:IEEE transactions on image processing 1997-03, Vol.6 (3), p.373-382
Main Authors: Popescu, D.C., Dimca, A., Hong Yan
Format: Article
Language:English
Subjects:
Adaptive coding
Applied sciences
Australia
Conformal mapping
Exact sciences and technology
Extraterrestrial measurements
Fractals
Image coding
Image processing
Information science
Information technology
Information, signal and communications theory
Signal processing
Solid modeling
Space technology
Telecommunications and information theory
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Summary:After a very promising start, progress in fractal image coding has been relatively slow recently. Most improvements have been concentrating on better adaptive coding algorithms and on search strategies to reduce the encoding time. Very little has been-done to challenge the linear model of the fractal transformations used so far in practical applications. In this paper, we explain why effective nonlinear transformations are not easy to find and propose a model based on conformal mappings in the geometric domain that are a natural extension of the affine model. Our compression results show improvements over the linear model and support the hope that a deeper understanding of the notion of self-similarity would further advance fractal image coding.
ISSN:1057-7149
1941-0042
DOI:10.1109/83.557339