Bayes risk-weighted vector quantization

Abstract

Lossy compression and classification algorithms both attempt to reduce a large collection of possible observations into a few representative categories so as to preserve essential information. A framework for combining classification and compression into one or two quantizers is described along with some examples and related to other quantizer-based classification schemes.