Title :
Permutative vector quantization-application to image compression
Author :
Skowronski, J. ; Dologlou, I.
Author_Institution :
Lab. des Signaux et Syst., CNRS, Gif-sur-Yvette, France
Abstract :
The paper describes the permutative vector quantization (PVQ) scheme as a special case of a more general structurally constrained vector quantization concept. This concept makes it possible to increase the vector dimensions beyond the technical bounds of conventional VQ and to exploit, by means of this, the inter-pixel correlations in large image blocks. Furthermore, a codebook design algorithm adapted to permutative VQ is proposed and it is shown experimentally that the coding performance of conventional VQ can be improved using the present scheme
Keywords :
correlation methods; image coding; vector quantisation; codebook design algorithm; image compression; inter-pixel correlations; permutative vector quantization; vector dimensions; Algorithm design and analysis; Books; Clustering algorithms; Data compression; Image coding; Nearest neighbor searches; Neural networks; Rate distortion theory; Statistics; Vector quantization;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.480078
