DocumentCode
956885
Title
Efficient video compression codebooks using SOM-based vector quantisation
Author
Ferguson, K.L. ; Allinson, N.M.
Author_Institution
Quay West Bus. Centre, Manchester, UK
Volume
151
Issue
2
fYear
2004
fDate
4/30/2004 12:00:00 AM
Firstpage
102
Lastpage
108
Abstract
A new rate-constrained self-organising map (SOM) learning algorithm, incorporating a noise-mixing model, is presented as a vector quantiser for very low bit-rate video codecs. A SOM-based approach will exhibit a higher resilience against local minima under low resolution conditions. Practical implementation details and results are also described.
Keywords
image resolution; learning (artificial intelligence); self-organising feature maps; vector quantisation; video codecs; video coding; low bit-rate video codec; noise-mixing model; rate-constrained self-organising map learning algorithm; vector quantisation; vector quantiser; video compression codebook; video resolution condition;
fLanguage
English
Journal_Title
Vision, Image and Signal Processing, IEE Proceedings -
Publisher
iet
ISSN
1350-245X
Type
jour
DOI
10.1049/ip-vis:20040195
Filename
1284905
Link To Document