A parallel decoding algorithm for IFS codes without transient behavior

Iterated function systems (IFSs) have received great attention in encoding and decoding fractal images. Barnsley (1988) has shown that IFSs for image compression can achieve a very high compression ratio for a single image. However, the major drawback of such a technique is the large computation loa...

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Veröffentlicht in:IEEE transactions on image processing Jg. 5; H. 3; S. 411 - 415
Hauptverfasser: PEI, S.-C, TSENG, C.-C, LIN, C.-Y
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.03.1996
Institute of Electrical and Electronics Engineers
Schlagworte:
Applied sciences
Bandwidth
Clouds
Data compression
Discrete cosine transforms
Exact sciences and technology
Extraterrestrial measurements
Fractals
Image coding
Image communication
Image processing
Information, signal and communications theory
Iterative decoding
Signal processing
Telecommunications and information theory
Performance evaluation
Computation time
Parallel algorithm
Fractal
Compression ratio
Image processing
Coding
Data compression
Decoding
ISSN:1057-7149
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Zusammenfassung:Iterated function systems (IFSs) have received great attention in encoding and decoding fractal images. Barnsley (1988) has shown that IFSs for image compression can achieve a very high compression ratio for a single image. However, the major drawback of such a technique is the large computation load required to both encode and decode a fractal image. We provide a novel algorithm to decode IFS codes. The main features of this algorithm are that it is very suitable for parallel implementation and has no transient behavior. Also, from the decoding process of this method we can understand the encoding procedure explicitly. One example is illustrated to demonstrate the quality of its performance.
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ISSN:1057-7149
DOI:10.1109/83.491315