Entropy-constrained high-resolution lattice vector quantization using a perceptually relevant distortion measure
2007 (English)In: CONFERENCE RECORD OF THE FORTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, VOLS 1-5, NEW YORK: IEEE , 2007, 2075-2079 p.Conference paper (Other academic)
In this paper we study high-resolution entropy-constrained coding using multidimensional companding. To account for auditory perception, we introduce a perceptual relevant distortion measure. We will derive a multidimensional companding function which is asymptotically optimal in the sense that the rate loss introduced by the compander will vanish with increasing vector dimension. We compare the companding scheme to a scheme which is based on a perceptual weighting of the source, thereby transforming the perceptual distortion measure into a mean-squared error distortion measure. Experimental results show that even at low vector dimension, the rate loss introduced by the compander is low (less than 0.05 bit per dimension in case of two-dimensional vectors).
Place, publisher, year, edition, pages
NEW YORK: IEEE , 2007. 2075-2079 p.
IdentifiersURN: urn:nbn:se:kth:diva-36118DOI: 10.1109/ACSSC.2007.4487603ISI: 000257172901131ScopusID: 2-s2.0-50249101074OAI: oai:DiVA.org:kth-36118DiVA: diva2:430566
41st Asilomar Conference on Signals, Systems and Computers Pacific Grove, CA, NOV 04-07, 2007
QC 201107112011-07-112011-07-082011-07-11Bibliographically approved