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

Verusca Severo1, Felipe B S Ferreira2, Rodrigo Spencer1

  • 1Polytechnic School of Pernambuco, University of Pernambuco, Recife 50720-001, Brazil.

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|April 27, 2024
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Novel initialization strategies significantly enhance Vector Quantization (VQ) codebook design. These methods improve image reconstruction quality and reduce codebook design time compared to random initialization.

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image compressioninitializationswarm intelligencevector quantization

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Area of Science:

  • Computer Science
  • Signal Processing
  • Artificial Intelligence

Background:

  • Vector Quantization (VQ) is crucial for signal processing, particularly in image compression.
  • The Linde-Buzo-Gray (LBG) algorithm is a standard for VQ codebook design, but its performance heavily relies on initial codebook selection.
  • Random initialization is common but often suboptimal for VQ codebook quality and convergence speed.

Purpose of the Study:

  • To evaluate the impact of novel initialization strategies on swarm intelligence-based VQ codebook design algorithms.
  • To assess the effectiveness of these strategies in improving codebook quality and convergence speed.
  • To compare combined initialization techniques against traditional random initialization.

Main Methods:

  • Investigated nine initialization strategies combining literature-based and random vector selection for VQ codebooks.
  • Applied these strategies to modified Firefly Algorithm-LBG (M-FA-LBG), Particle Swarm Optimization-LBG (M-PSO-LBG), and Fish School Search-LBG (M-FSS-LBG) algorithms, including accelerated versions.
  • Evaluated codebook quality using Peak Signal-to-Noise Ratio (PSNR) for reconstructed images and convergence speed by iteration count.

Main Results:

  • Proposed initialization strategies demonstrated significant improvements over random initialization.
  • Achieved gains up to 4.43 dB in PSNR for the 'Clock' image using M-PSO-LBG with 512 codebooks.
  • Reported codebook design time savings of up to 67.05% for the 'Clock' image with M-FF-LBGa (accelerated Firefly Algorithm-LBG) and 512 codebooks.

Conclusions:

  • Initialization strategies offer a promising approach to enhance VQ codebook design.
  • Combining different initialization techniques can lead to superior codebook quality and faster convergence.
  • The findings support the adoption of these advanced initialization methods for swarm intelligence-based VQ algorithms.