On Distribution Preserving Quantization
(English)Manuscript (preprint) (Other academic)
Upon compressing perceptually relevant signals, conventional quantization generally results in unnaturaloutcomes at low rates. We propose distribution preserving quantization (DPQ) to solve this problem.DPQ is a new quantization concept that confines the probability space of the reconstruction to be identicalto that of the source. A distinctive feature of DPQ is that it facilitates a seamless transition between signalsynthesis and quantization. A theoretical analysis of DPQ leads to a distribution preserving rate-distortionfunction (DP-RDF), which serves as a lower bound on the rate of any DPQ scheme, under a constrainton distortion. In general situations, the DP-RDF approaches the classic rate-distortion function for thesame source and distortion measure, in the limit of an increasing rate. A practical DPQ scheme basedon a multivariate transformation is also proposed. This scheme asymptotically achieves the DP-RDF fori.i.d. Gaussian sources and the mean squared error.
Distribution preserving quantization, Rate-distortion function, Shannon lower bound
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-38515OAI: oai:DiVA.org:kth-38515DiVA: diva2:437187
QC 201108292011-08-292011-08-262011-08-29Bibliographically approved