Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding
Science Journal of Circuits, Systems and Signal Processing
Volume 3, Issue 6-1, December 2014, Pages: 17-23
Received: Nov. 1, 2014; Accepted: Nov. 5, 2014; Published: Nov. 12, 2014
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Kakalakannan Damodharan, Department of Electronics and Communication Engineering, Theja Sakthi Institute of Technology for Women, Coimbatore, Tamilnadu, India
Thamarai Muthusamy, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore, Tamilnadu, India
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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.
Motion Vector, Sum Absolute Difference, Average Mean Square Error, Full Search Algorithms, Particle Swarm Optimization, Directed Particle swarm Optimization, Block Matching Algorithm, Memetic PSO, Mutation Simplex PSO
To cite this article
Kakalakannan Damodharan, Thamarai Muthusamy, Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding, Science Journal of Circuits, Systems and Signal Processing. Special Issue: Computational Intelligence in Digital Image Processing. Vol. 3, No. 6-1, 2014, pp. 17-23. doi: 10.11648/j.cssp.s.2014030601.13
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