DocumentCode :
1508470
Title :
Fuzzy relational compression
Author :
Hirota, Kaoru ; Pedrycz, Witold
Author_Institution :
Dept. of Comput. Intelligence & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan
Volume :
29
Issue :
3
fYear :
1999
fDate :
6/1/1999 12:00:00 AM
Firstpage :
407
Lastpage :
415
Abstract :
This study concentrates on fuzzy relational calculus regarded as a basis of data compression. In this setting, images are represented as fuzzy relations. We investigate fuzzy relational equations as a basis of image compression. It is shown that both compression and decompression (reconstruction) phases are closely linked with the way in which fuzzy relational equations are being usually set and solved. The theoretical findings encountered in the theory of these equations are easily accommodated as a backbone of the relational compression. The character of the solutions to the equations make them ideal for reconstruction purposes as they specify the extremal elements of the solution set and in such a way help establish some envelopes of the original images under compression. The flexibility of the conceptual and algorithmic framework arising there is also discussed. Numerical examples provide a suitable illustrative material emphasizing the main features of the compression mechanisms
Keywords :
data compression; image coding; image reconstruction; relational algebra; data compression; fuzzy relational calculus; fuzzy relations; image compression; reconstruction; relational compression; Calculus; Data compression; Equations; Fuzzy sets; Image coding; Image processing; Image reconstruction; Solids; Spine; Vehicles;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4419
Type :
jour
DOI :
10.1109/3477.764876
Filename :
764876
Link To Document :
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