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Spammer Classification Using Ensemble Methods over Content-Based Features Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Parameter Optimization for H.265/HEVC Encoder Using NSGA II

Authors : Saurav Kumar, Satvik Gupta, Vishvender Singh, Mohit Khokhar, Prashant Singh Rana

Published in: Proceedings of Sixth International Conference on Soft Computing for Problem Solving

Publisher: Springer Singapore

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Abstract

High Efficiency Video Coding (H.265/HEVC) is the latest technology standard proposed by Joint Collaborative Team on Video Coding (JCT-VC). There are quite a few parameters for this encoder required to accomplish this goal. If a single standard configuration file is used for all genres of videos that may not maintain the optimal quality in all encoded videos. This is because every video has objects with unlike speeds of movement. Therefore, encoding factors must be customized in the most favorable way for each video separately. The work propose here is to use NSGA II for multi-objective optimization in order to find out the respective personalized encoding parameters to obtain higher Compression Ratio and Peak Signal-to-Noise Ratio (PSNR). Experiments on six QCIF videos with resolution \(176\times 144\) and different configuration files have been performed. Results demonstrate that the proposed technique gives enhanced video compression quality. Test videos and code used in the research is available as supplement at http://​bit.​ly/​HEVC-NSGA-II.

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Metadata
Title
Parameter Optimization for H.265/HEVC Encoder Using NSGA II
Authors
Saurav Kumar
Satvik Gupta
Vishvender Singh
Mohit Khokhar
Prashant Singh Rana
Copyright Year
2017
Publisher
Springer Singapore
Book
Proceedings of Sixth International Conference on Soft Computing for Problem Solving

Print ISBN: 978-981-10-3324-7

Electronic ISBN: 978-981-10-3325-4

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-3325-4_11

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