Optimised feature map finite-state vector quantisation for image coding

C. Zhu, L. M. Po, Y. Hua

Research output: Journal Publications and ReviewsRGC 22 - Publication in policy or professional journal

1 Citation (Scopus)

Abstract

An optimised feature map finite-state vector quantisation (referred to as optimised FMFSVQ) is presented for image coding. Based on the block-based gradient descent search algorithm used for motion estimation in video coding, the optimised FMFSVQ system finds a neighbourhood-based optimal codevector for each input vector by extending the associated state codebook stage by stage, thus rendering each state quantiser a variable rate vector quantisation. The optimised FMFSVQ system can be interpreted as a cascade of a finite-state vector quantiser and classified vector quantisers. Furthermore, an adaptive optimised FMFSVQ is obtained. Experiments demonstrate the superior rate-distortion performance of the adaptive optimised FMFSVQ compared with the original adaptive FMFSVQ and the memoryless vector quantisation. © IEE, 2000.
Original languageEnglish
Pages (from-to)266-270
JournalIEE Proceedings: Vision, Image and Signal Processing
Volume147
Issue number3
DOIs
Publication statusPublished - Jun 2000

Fingerprint

Dive into the research topics of 'Optimised feature map finite-state vector quantisation for image coding'. Together they form a unique fingerprint.

Cite this