DocumentCode
304467
Title
Neural networks and semi-closed-loop predictive vector quantization for image compression
Author
Cierniak, Robert ; Rutkowski, Leszek
Author_Institution
Inst. of Electron. & Control Syst., Tech. Univ. of Czestochowa, Poland
Volume
1
fYear
1996
fDate
16-19 Sep 1996
Firstpage
245
Abstract
A new algorithm for image compression, named predictive vector quantization (PVQ), is developed based on competitive neural networks and optimal linear predictors. The semi-closed-loop PVQ methodology is suggested. The experimental results are presented and the performance of the algorithm is discussed
Keywords
differential pulse code modulation; image coding; neural nets; prediction theory; unsupervised learning; vector quantisation; DPCM; PVQ; algorithm performance; competitive neural networks; differential pulse code modulation; experimental results; image compression; optimal linear predictors; semiclosed-loop predictive vector quantization; Control systems; Decoding; Electronic mail; Image coding; Image reconstruction; Modulation coding; Neural networks; Pixel; Pulse modulation; Vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1996. Proceedings., International Conference on
Conference_Location
Lausanne
Print_ISBN
0-7803-3259-8
Type
conf
DOI
10.1109/ICIP.1996.559479
Filename
559479
Link To Document