Multi objective Particle Swarm Optimization in video coding
M. Thamarai1, R. Shanmugalakshmi2
1M.Thamarai, ECE Depatment, Karpagam college of Enineering, Coimbatore, Tamilnadu, .India.
2Dr.R.Shanmugalakshmi, Department of CSE, Government College of Technology, Coimbatore, Tami nadu, India.
Manuscript received on January 01, 2013. | Revised Manuscript received on January 02, 2013. | Manuscript published on January 05, 2013. | PP: 419-423 | Volume-2, Issue-6, January 2013. | Retrieval Number: F1243112612/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Particle Swarm Optimization (PSO) is a global optimization technique based on swarm intelligence. It simulates the behavior of bird flocking. It is widely accepted and focused by researchers due to its profound intelligence and simple algorithm structure. Currently PSO has been implemented in a wide range of research areas such as functional optimization, pattern recognition, neural network training and fuzzy system control etc., and obtained significant success. In this paper the application of Particle swarm optimization for video coding is analyzed The application of multi objective optimization using PSO for optimal subband selection of the dualtree discrete wavelet transform is proposed and analyzed. The results are compared with the standard techniques. The video coding using PSO and Dualtree wavelet transform provides better PSNR values when compared to the PSO based Block based coders. The performance variation of the PSO based coder in various aspects such as swarm size variation and threshold value variation for frame rates are also measured.
Keywords: Dualtree Discrete Wavelet Transform, Multi objective Particle Swarm Optimization, Noise Shaping and MSE