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.,. In video processing PSO is used to find the best matching block in Block matching algorithm, bit rate optimization for MPEG 1/2, object tracking and data clustering. In this paper the usage of PSO in Block matching algorithms for video compression is analyzed and the results are compared with the existing techniques.
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