|Enhance the Performance of Video Compression Based on Fractal H-V Partition Technique with Particle Swarm Optimization|
|Shraddha Pandit1 , Piyush Kumar Shukla2 , Akhilesh Tiwari3|
1 University Institute of Technology, RGPV, Bhopal, India.
2 Department of Computer Science and Engineering, UIT-RGPV, Bhopal, India.
3 Department of CSE & IT, Madhav Institute of Technology and Science (MITS), Gwalior, India.
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Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-1 , Page no. 31-35, Jan-2018
Online published on Jan 31, 2018
Copyright © Shraddha Pandit, Piyush Kumar Shukla, Akhilesh Tiwari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Shraddha Pandit, Piyush Kumar Shukla, Akhilesh Tiwari, “Enhance the Performance of Video Compression Based on Fractal H-V Partition Technique with Particle Swarm Optimization”, International Journal of Computer Sciences and Engineering, Vol.6, Issue.1, pp.31-35, 2018.
MLA Style Citation: Shraddha Pandit, Piyush Kumar Shukla, Akhilesh Tiwari "Enhance the Performance of Video Compression Based on Fractal H-V Partition Technique with Particle Swarm Optimization." International Journal of Computer Sciences and Engineering 6.1 (2018): 31-35.
APA Style Citation: Shraddha Pandit, Piyush Kumar Shukla, Akhilesh Tiwari, (2018). Enhance the Performance of Video Compression Based on Fractal H-V Partition Technique with Particle Swarm Optimization. International Journal of Computer Sciences and Engineering, 6(1), 31-35.
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|The searching of coefficient and blocks in video compression is important phase. For the searching of blocks and coefficient used zig-zag and some other random searching technique for symmetry of blocks. In this paper used particle swarm optimization for the searching of block coefficient in domain and range of fractal transform function. The particle swarm optimization enhances the searching capacity of encoder for the process of compression. The particle swarm optimization decides two dual functions one for the mapping of symmetry and other is mapping of video encoded block. For the process of fractal transform encoding used H-V partition technique. H-V partition technique mapped the data in terms of range and domain for the processing of video compression. The H-V partition process creates multiple rectangle blocks the processing of video. The process of video compression methods simulated in MATLAB software and used some standard parameters for the evaluation of compression results.|
|Key-Words / Index Term :|
|Video Compression, Fractal Transform, H-V partitioning, MATLAB, MSE|
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