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Hybrid firefly-Linde-Buzo-Gray algorithm for Channel-Optimized Vector Quantization codebook design
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DOI：10.3233/ICA-170546.png)
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Abstract
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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
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