NDLI: Fuzzy vector quantization algorithms and their application in image compression

Content Provider	IEEE Xplore Digital Library
Author	Karayiannis, N.B. Pai, P.-I.
Copyright Year	1992
Abstract	This paper presents the development and evaluation of fuzzy vector quantization algorithms. These algorithms are designed to achieve the quality of vector quantizers provided by sophisticated but computationally demanding approaches, while capturing the advantages of the frequently used in practice k-means algorithm, such as speed, simplicity, and conceptual appeal. The uncertainty typically associated with clustering tasks is formulated in this approach by allowing the assignment of each training vector to multiple clusters in the early stages of the iterative codebook design process. A training vector assignment strategy is also proposed for the transition from the fuzzy mode, where each training vector can be assigned to multiple clusters, to the crisp mode, where each training vector can be assigned to only one cluster. Such a strategy reduces the dependence of the resulting codebook on the random initial codebook selection. The resulting algorithms are used in image compression based on vector quantization. This application provides the basis for evaluating the computational efficiency of the proposed algorithms and comparing the quality of the resulting codebook design with that provided by competing techniques.<>
Sponsorship	IEEE Signal Processing Society
Starting Page	1193
Ending Page	1201
Page Count	9
File Size	1153724
File Format	PDF
ISSN	10577149
Volume Number	4
Issue Number	9
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-09-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Image coding Iterative algorithms Clustering algorithms Partitioning algorithms Algorithm design and analysis Image storage Image reconstruction Distortion measurement Uncertainty
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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