DocumentCode :
2605954
Title :
Feature based compression of vector quantized codebooks and data for optimal image compression
Author :
Knutson, Jack R. ; Choo, Chang Y.
Author_Institution :
Dept. of Electr. Eng., San Jose State Univ., CA, USA
fYear :
1993
fDate :
3-6 May 1993
Firstpage :
691
Abstract :
The Linde-Buzo-Gray (LBG) algorithm is a procedure in vector quantization. An attempt is made to compress the LBG codebook by simple feature-based clustering. The centroids of the resulting clusters form a reduced LBG codebook. The resulting reduced LBG codebook has almost identical SNR as the equivalent size original LBG codebook. Several other experimental results are presented which show that the above clustering technique may be applied directly to the original images in order to find an initial codebook for LBG codebook training, or to quickly generate an alternative codebook with comparable quality
Keywords :
feature extraction; image coding; vector quantisation; LBG codebook; Linde-Buzo-Gray algorithm; SNR; centroids; clustering technique; feature-based clustering; initial codebook; optimal image compression; vector quantized codebooks; Algorithm design and analysis; Books; Clustering algorithms; Data compression; Goniometers; Image coding; Lifting equipment; Signal to noise ratio; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
Type :
conf
DOI :
10.1109/ISCAS.1993.393815
Filename :
393815
Link To Document :
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