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