DocumentCode :
1584663
Title :
Image compression using iterated function systems and revolutionary programming: image compression without image metrics
Author :
Hoskins, Douglas A. ; Vagners, Juris
Author_Institution :
Dept. of Aeronaut. & Astronaut., Washington Univ., Seattle, WA, USA
fYear :
1992
Firstpage :
705
Abstract :
A method which generates a compressed form for an input image without explicit reference to any complete image metrics is presented. The compressed form of the image is an iterated function system (IFS). The IFS is generated using an evolutionary programming optimization. This optimization simulates the competitive dynamics on an array of mapping cells. The result of the competition is a minimal number of parameters (mappings) which characterize the image. Because these parameters are calculated without using the overall image, it is believed that this method could lead to procedures for identifying objects without first segmenting them from their surroundings
Keywords :
data compression; image processing; iterative methods; optimisation; programming; competitive dynamics; input image; iterated function system; iterated function systems; mapping cells array; mappings; optimization; parameters; revolutionary programming; Fractals; Functional programming; Genetic programming; Image coding; Image generation; Image recognition; Image segmentation; Machine vision; Object recognition; Polynomials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
ISSN :
1058-6393
Print_ISBN :
0-8186-3160-0
Type :
conf
DOI :
10.1109/ACSSC.1992.269104
Filename :
269104
Link To Document :
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