PSO Algorithm Applied to Codebook Design for Channel-Optimized Vector Quantization

• Published in: Revista IEEE América Latina Vol. 13; no. 4; pp. 961 - 967
• Main Authors: Alberico Sa Leitao, Herbert, Terllizzie Araujo Lopes, Waslon, Madeiro, Francisco
• Format: Journal Article
• Language: English
• Published: Los Alamitos IEEE 01.04.2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Boats; channel-optimized vector quantization; Channels; Clocks; Computer simulation; Design engineering; Image coding; Image reconstruction; Image transmission; image vector quantization; Irrigation; Particle swarm optimization; Robustness; signal processing; Swarm intelligence; Vector quantization
• ISSN: 1548-0992; 1548-0992
• DOI: 10.1109/TLA.2015.7106343

Vector quantization (VQ) has been used in signal compression systems. However, in the scenario of image transmission, VQ is very sensitive to channel errors. An approach to decrease such sensitivity is channel-optimized vector quantization (COVQ), which involves VQ codebook design taking into account the characteristics of the channel. In the present work, particle swarm optimization (PSO) is applied to codebook design for COVQ. Simulation results are presented for a variety of bit error rates of a binary symmetric channel (BSC) and reveal the effectiveness of the method in decreasing visual impairment by blocking artifacts in the reconstructed images, overperforming conventional COVQ codebook design in terms of peak signal to noise ratio of the reconstructed images for approximately 90% of exhaustive evaluations of image transmission over BSC.