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Video Coding Using Directed Particle Swarm Optimization

M. Thamarai, Dr. R. Shanmugalakshmi

Abstract


Particle Swarm Optimization (PSO) is 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. Particle Swarm Optimization (PSO) recently has been successfully applied to perform block-based motion estimation. In this paper, a modified version of PSO called Directed PSO (DPSO) is proposed for video coding. In this modified version, we have proposed a new parameter called Velocity Rate (VR) for changing the position of the particles, and the particles are replaced insensitive with the direction also. The experimental results show that DPSO reduces the computational complexity and increases the performance of motion estimation while comparing with other exiting algorithms.

Keywords


Block Matching, Video Coding, Particle Swarm Optimization.

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References


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