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A Feature Based Complexity Model for Decoder Complexity Optimized HEVC Video Encoding

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conference contribution
posted on 2022-04-29, 08:52 authored by Thanuja MallikarachchiThanuja Mallikarachchi, Dumidu S. Talagala, Hemantha Kodikara Arachchi, Anil Fernando

The complexity of the novel video compression algorithms is a major contributor for the increased demand of processing and energy resources for video playback in consumer electronic devices. Therefore, a decoder complexity reduction mechanism is proposed which constitutes a model that predicts the decoder's complexity requirements to decode the HEVC encoded bit streams with a 4.2% average prediction error and a decoder complexity optimized encoding algorithm, which reduces the decoding complexity by an average of 28.06% and 41.19% with a -1.91 dB and -2.46 dB impact to the BD-PSNR for the low delay P and random access configurations, respectively. 

History

Presented at

Conference paper published in 2017 IEEE International Conference on Consumer Electronic (ICCE), available at: https://doi.org/10.1109/ICCE.2017.7889357.

Published in

2017 IEEE International Conference on Consumer Electronics (ICCE)

Publisher

IEEE

Version

  • AM (Accepted Manuscript)

Citation

Mallikarachchi, T., Talagala, D.S., Fernando, A. and Kodikara Arachchi, H. (2017) 'A Feature Based Complexity Model for Decoder Complexity Optimized HEVC Video Encoding', IEEE International Conference on Consumer Electronic (ICCE), Las Vegas, USA, 8-10 January. DOI: 10.1109/ICCE.2017.7889357.

Electronic ISSN

2158-4001

ISBN

978-1-5090-5544-9

Cardiff Met Affiliation

  • Cardiff School of Technologies

Cardiff Met Authors

Thanuja Mallikarachchi

Copyright Holder

  • © The Publisher

Publisher Rights Statement

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Language

  • en

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