Fast vector quantization using a Bat algorithm for image compression

Linde-Buzo-Gray (LBG), a traditional method of vector quantization (VQ) generates a local optimal codebook which results in lower PSNR value. The performance of vector quantization (VQ) depends on the appropriate codebook, so researchers proposed optimization techniques for global codebook generatio...

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Detalhes bibliográficos
Autores: Chiranjeevi, Karri, Jena, Umaranjan R.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2016
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/72688
Acesso em linha:https://hdl.handle.net/10230/72688
http://dx.doi.org/10.1016/j.jestch.2015.11.003
Access Level:acceso abierto
Palavra-chave:Vector quantization
Linde-Buzo-Gray (LBG)
Particle swarm optimization (PSO)
Quantum particle swarm algorithm (QPSO)
Honey bee mating optimization (HBMO)
Firefly algorithm (FA)
Bat algorithm (BA)
Descrição
Resumo:Linde-Buzo-Gray (LBG), a traditional method of vector quantization (VQ) generates a local optimal codebook which results in lower PSNR value. The performance of vector quantization (VQ) depends on the appropriate codebook, so researchers proposed optimization techniques for global codebook generation. Particle swarm optimization (PSO) and Firefly algorithm (FA) generate an efficient codebook, but undergoes instability in convergence when particle velocity is high and non-availability of brighter fireflies in the search space respectively. In this paper, we propose a new algorithm called BA-LBG which uses Bat Algorithm on initial solution of LBG. It produces an efficient codebook with less computational time and results very good PSNR due to its automatic zooming feature using adjustable pulse emission rate and loudness of bats. From the results, we observed that BA-LBG has high PSNR compared to LBG, PSO-LBG, Quantum PSO-LBG, HBMO-LBG and FA-LBG, and its average convergence speed is 1.841 times faster than HBMO-LBG and FA-LBG but no significance difference with PSO.