Study on the effect of neighbourhood functions for noise robust vector quantizers

Abstract

By the use of noise robust compression, separate error correction can be reduced. This paper studies a number of neighbourhood functions for the SOFM for designing image vector quantizer codebooks for noisy channels. They include a neighbourhood recently proposed for the scalar coding of speech and a novel neighbourhood which makes the SOFM functionally equivalent to the popular LBG algorithm. The simulation results of these neighbourhood functions on two images provide insight into the problem of selecting an appropriate topology for the design of vector quantizer codebooks for noisy channels.