DocumentCode
1082580
Title
Image coding using feature map finite-state vector quantization
Author
Xu, Meina ; Kuh, Anthony
Author_Institution
Dept. of Electr. Eng., Hawaii Univ., Honolulu, HI, USA
Volume
3
Issue
7
fYear
1996
fDate
7/1/1996 12:00:00 AM
Firstpage
215
Lastpage
217
Abstract
A vector quantization (VQ) scheme with finite memory called feature map finite-state vector quantization (FMFSVQ) is presented. The FMFSVQ takes advantage of good topological ordering so that the design of state codebooks is simplified. Our FMFSVQ also has no duplication of state codebooks, no synchronization required between encoder and decoder, and a very simple decoder. An adaptive FMFSVQ scheme is also proposed. Experimental results are presented for different super codebook sizes and different state codebook sizes.
Keywords
image coding; self-organising feature maps; unsupervised learning; vector quantisation; FMFSVQ; decoder; encoder; experimental results; feature map finite-state vector quantization; image coding; state codebook sizes; state codebooks design; supercodebook sizes; topological ordering; unsupervised learning; Bit rate; Computational complexity; Decoding; Feature extraction; Histograms; Image coding; Indexing; Transmitters; Unsupervised learning; Vector quantization;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/97.508169
Filename
508169
Link To Document