DocumentCode
1434846
Title
Index-compressed vector quantisation based on index mapping
Author
Shanbehzadeh, J. ; Ogunbona, P.O.
Author_Institution
Dept. of Electr. & Comput. Eng., Wollongong Univ., NSW, Australia
Volume
144
Issue
1
fYear
1997
fDate
2/1/1997 12:00:00 AM
Firstpage
31
Lastpage
38
Abstract
The authors introduce a novel coding technique which significantly improves the performance of the traditional vector quantisation (VQ) schemes at low bit rates. High interblock correlation in natural images results in a high probability that neighbouring image blocks are mapped to small subsets of the VQ codebook, which contains highly correlated codevectors. If, instead of the whole VQ codebook, a small subset is considered for the purpose of encoding neighbouring blocks, it is possible to improve the performance of traditional VQ schemes significantly. The performance improvement obtained with the new method is about 3 dB on average when compared with traditional VQ schemes at low bit rates. The method provides better performance than the JPEG coding standard at low bit rates, and gives comparable results with much less complexity than address VQ
Keywords
correlation methods; image coding; vector quantisation; JPEG coding standard; VQ codebook; complexity; correlated codevectors; high interblock correlation; image coding; index-compressed vector quantisation; low bit rates; neighbouring image blocks encoding; performance;
fLanguage
English
Journal_Title
Vision, Image and Signal Processing, IEE Proceedings -
Publisher
iet
ISSN
1350-245X
Type
jour
DOI
10.1049/ip-vis:19970984
Filename
570028
Link To Document