Algoritmo PSO Aplicado ao Projeto de Dicionários para Quantização Vetorial Otimizada para Canal (PSO Algorithm Applied to Codebook Design for Channel-Optimized Vector Quantization)

Herbert Albérico Sá Leitão (herbert.leitao@ufpe.br)1, Waslon Terllizzie Araújo Lopes (waslon@ieee.org)2, Francisco Madeiro ( madeiro@poli.br)3


1Universidade Federal de Pernambuco
2Universidade Federal de Campina Grande
3Universidade Federal da Paraíba - UFPB

This paper appears in: Revista IEEE América Latina

Publication Date: April 2015
Volume: 13,   Issue: 4 
ISSN: 1548-0992


Abstract:
Vector quantization (VQ) has been used in signal compression systems. However, in the scenario of image transmission, VQ is very sensitive to channel errors. An approach to decrease such sensitivity is channel-optimized vector quantization (COVQ), which involves VQ codebook design taking into account the characteristics of the channel. In the present work, particle swarm optimization (PSO) is applied to codebook design for COVQ. Simulation results are presented for a variety of bit error rates of a binary symmetric channel (BSC) and reveal the effectiveness of the method in decreasing visual impairment by blocking artifacts in the reconstructed images, overperforming conventional COVQ codebook design in terms of peak signal to noise ratio of the reconstructed images for approximately 90% of exhaustive evaluations of image transmission over BSC.

Index Terms:
image vector quantization, channel-optimized vector quantization, particle swarm optimization, signal processing   


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