On the Initialization of Swarm Intelligence Algorithms for Vector Quantization Codebook Design

Verusca Severo; Felipe B S Ferreira; Rodrigo Spencer; Arthur Nascimento; Francisco Madeiro

doi:10.3390/s24082606

On the Initialization of Swarm Intelligence Algorithms for Vector Quantization Codebook Design

Sensors (Basel). 2024 Apr 19;24(8):2606. doi: 10.3390/s24082606.

Authors

Verusca Severo¹, Felipe B S Ferreira², Rodrigo Spencer¹, Arthur Nascimento¹, Francisco Madeiro¹

Affiliations

¹ Polytechnic School of Pernambuco, University of Pernambuco, Recife 50720-001, Brazil.
² Engineering Campus, Rural Federal University of Pernambuco, Cabo de Santo Agostinho 54518-430, Brazil.

Abstract

Vector Quantization (VQ) is a technique with a wide range of applications. For example, it can be used for image compression. The codebook design for VQ has great significance in the quality of the quantized signals and can benefit from the use of swarm intelligence. Initialization of the Linde-Buzo-Gray (LBG) algorithm, which is the most popular VQ codebook design algorithm, is a step that directly influences VQ performance, as the convergence speed and codebook quality depend on the initial codebook. A widely used initialization alternative is random initialization, in which the initial set of codevectors is drawn randomly from the training set. Other initialization methods can lead to a better quality of the designed codebooks. The present work evaluates the impacts of initialization strategies on swarm intelligence algorithms for codebook design in terms of the quality of the designed codebooks, assessed by the quality of the reconstructed images, and in terms of the convergence speed, evaluated by the number of iterations. Initialization strategies consist of a combination of codebooks obtained by initialization algorithms from the literature with codebooks composed of vectors randomly selected from the training set. The possibility of combining different initialization techniques provides new perspectives in the search for the quality of the VQ codebooks. Nine initialization strategies are presented, which are compared with random initialization. Initialization strategies are evaluated on the following algorithms for codebook design based on swarm clustering: modified firefly algorithm-Linde-Buzo-Gray (M-FA-LBG), modified particle swarm optimization-Linde-Buzo-Gray (M-PSO-LBG), modified fish school search-Linde-Buzo-Gray (M-FSS-LBG) and their accelerated versions (M-FA-LBGa, M-PSO-LBGa and M-FSS-LBGa) which are obtained by replacing the LBG with the accelerated LBG algorithm. The simulation results point out to the benefits of the proposed initialization strategies. The results show gains up to 4.43 dB in terms of PSNR for image Clock with M-PSO-LBG codebooks of size 512 and codebook design time savings up to 67.05% for image Clock, with M-FF-LBGa codebooks with size N=512, by using initialization strategies in substitution to Random initialization.

Keywords: image compression; initialization; swarm intelligence; vector quantization.

Grants and funding

This research was funded by Fundação Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Fundação de Amparo a Ciência e Tecnologia de Pernambuco (FACEPE) and Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).