Hybrid firefly-Linde-Buzo-Gray algorithm for Channel-Optimized Vector Quantization codebook design

Article type: Research Article

Authors: Ferreira, Felipe A.B.S.^a | Leitão, Herbert A.S.^b | Lopes, Waslon T.A.^{c; *} | Madeiro, Francisco^a

Affiliations: [a] Polytechnic School of Pernambuco, University of Pernambuco, Recife, Pernambuco, Brazil | [b] Department of Electrical Engineering, Federal University of Pernambuco, Recife, Pernambuco, Brazil | [c] Department of Electrical Engineering, Federal University of Paraíba, João Pessoa, Paraíba, Brazil

Correspondence: [*] Corresponding author: Waslon T.A. Lopes, Department of Electrical Engineering, Federal University of Paraíba, João Pessoa, Paraíba, Brazil. E-mail: [email protected].

Abstract: This paper introduces a hybrid method that uses Firefly Algorithm (FA) and Linde-Buzo-Gray (LBG) algorithm to Channel-Optimized Vector Quantization (COVQ) codebook design. Fast nearest neighbor search (NNS) techniques are used with the purpose of execution time savings of the proposed COVQ codebook design. Simulation results concerning image transmission over a binary symmetric channel (BSC) reveal the superiority of the proposed swarm intelligence technique, referred to as FA-COVQ, over conventional COVQ codebook design method. Simulation results also reveal that the adoption of acceleration techniques in FA-COVQ codebook design can lead to execution time savings up to about 97% when compared to the FA-COVQ with brute force approach.

Keywords: Image compression, Vector Quantization, Channel-Optimized Vector Quantization, swarm clustering algorithm, Firefly Algorithm

DOI: 10.3233/ICA-170546

Journal: Integrated Computer-Aided Engineering, vol. 24, no. 3, pp. 297-314, 2017