Modified firefly algorithm applied to image vector quantisation codebook design. (2016)

• Record Type: Journal Article
• Authors: Severo, V.; LeitÁ£o, H.A.S.; Lima, J.B.; Lopes, W.T.A.; Madeiro, F.
• Is Part Of: International journal of innovative computing and applications. Volume 7:Number 4(2016)
• Page Start: 202
• Page End: 213
• Publication Date: 2016
• Subjects: image vector quantisation -- image compression -- codebook design -- firefly algorithm -- signal processing -- simulation -- image reconstruction -- peak SNR -- PSNR -- signal to noise ratio; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

Vector quantisation (VQ) has been used in signal processing applications, such as steganography, watermarking and signal compression. The performance of signal processing systems based on VQ depends on the designed codebooks. In the present work, modifications are introduced in the firefly algorithm - Linde-Buzo-Gray (FA-LBG) for the purpose of VQ codebook design. The modified version differs from the original one mainly for attempting to assure a stronger influence of the training set in codebook design. In the scenario of image vector quantisation, simulation results show that the modified algorithm outperforms both the original one as well as the traditional LBG algorithm in terms of codebook quality, assessed by the peak signal to noise ratio of the reconstructed images. Additionally, alternatives are presented to accelerate the proposed algorithm, which lead to execution time savings up to 90%.