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.
| Published in |
Science Journal of Circuits, Systems and Signal Processing (Volume 3, Issue 6-1)
This article belongs to the Special Issue Computational Intelligence in Digital Image Processing |
| DOI | 10.11648/j.cssp.s.2014030601.13 |
| Page(s) | 17-23 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2014. Published by Science Publishing Group |
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
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APA Style
Kakalakannan Damodharan, Thamarai Muthusamy. (2014). Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding. Science Journal of Circuits, Systems and Signal Processing, 3(6-1), 17-23. https://doi.org/10.11648/j.cssp.s.2014030601.13
ACS Style
Kakalakannan Damodharan; Thamarai Muthusamy. Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding. Sci. J. Circuits Syst. Signal Process. 2014, 3(6-1), 17-23. doi: 10.11648/j.cssp.s.2014030601.13
AMA Style
Kakalakannan Damodharan, Thamarai Muthusamy. Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding. Sci J Circuits Syst Signal Process. 2014;3(6-1):17-23. doi: 10.11648/j.cssp.s.2014030601.13
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Download@article{10.11648/j.cssp.s.2014030601.13,
author = {Kakalakannan Damodharan and Thamarai Muthusamy},
title = {Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding},
journal = {Science Journal of Circuits, Systems and Signal Processing},
volume = {3},
number = {6-1},
pages = {17-23},
doi = {10.11648/j.cssp.s.2014030601.13},
url = {https://doi.org/10.11648/j.cssp.s.2014030601.13},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.s.2014030601.13},
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.,. 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.},
year = {2014}
}
TY - JOUR T1 - Analysis of Particle Swarm Optimization in Block Matching Algorithms for Video Coding AU - Kakalakannan Damodharan AU - Thamarai Muthusamy Y1 - 2014/11/12 PY - 2014 N1 - https://doi.org/10.11648/j.cssp.s.2014030601.13 DO - 10.11648/j.cssp.s.2014030601.13 T2 - Science Journal of Circuits, Systems and Signal Processing JF - Science Journal of Circuits, Systems and Signal Processing JO - Science Journal of Circuits, Systems and Signal Processing SP - 17 EP - 23 PB - Science Publishing Group SN - 2326-9073 UR - https://doi.org/10.11648/j.cssp.s.2014030601.13 AB - 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. VL - 3 IS - 6-1 ER -
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