DocumentCode
284867
Title
Stochastic vector quantization of images
Author
Torres, L. ; Arias, E.
Author_Institution
Dept. of Signal Theory & Commun., Univ. Politechnica de Cataluna, Barcelona, Spain
Volume
3
fYear
1992
fDate
23-26 Mar 1992
Firstpage
385
Abstract
The vector quantization scheme has proven to be very effective in image coding. One of the most important steps in the whole process is the design of the codebook. The codebook is generally designed using the Linde-Buzo-Gray algorithm, which is in essence a clustering algorithm that uses a large training set of empirical data that are statistically representative of the image to be quantized. The problem addressed is the stochastic generation of the codebook. The approach is to model the codebook according to some previous model defined for the image to be encoded and then to generate the training set according to the same model and not according to some specific data sequence. The model used is the well-known autoregressive model. Good visual results are shown in the range of 0.5-0.8 b/pixel
Keywords
image coding; stochastic processes; vector quantisation; autoregressive model; image coding; stochastic codebook generation; training set; Algorithm design and analysis; Clustering algorithms; Code standards; Image coding; Pixel; Process design; Speech coding; Statistics; Stochastic processes; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location
San Francisco, CA
ISSN
1520-6149
Print_ISBN
0-7803-0532-9
Type
conf
DOI
10.1109/ICASSP.1992.226220
Filename
226220
Link To Document