Real-Time Implementation of Scalable Hevc Encoder

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Abstract

This paper presents the first known open-source Scalable HEVC (SHVC) encoder for real-time applications. Our proposal is built on top of Kvazaar HEVC encoder by extending its functionality with spatial and signal-to-noise ratio (SNR) scalable coding schemes. These two scalability schemes have been optimized for real-time coding by means of three parallelization techniques: 1) wavefront parallel processing (WPP); 2) overlapped wavefront (OWF); and 3) AVX2-optimized upsampling. On an 8-core Xeon W-2145 processor, the proposed spatially scalable Kvazaar can encode twolayer 1080p video above 50 fps with scaling ratios of l.5 and 2. The respective coding gain s are 18.4% and 9.9% over Kvazaar simulcast coding at similar speed. Correspondingly, the coding speed of SNR scalable Kvazaar exceeds 30 fps with two-layer 1080p video. On average, it obtain s1.20 times speedup and 17.0% better coding efficiency over the simulcast case. These results justify the benefits of the proposed scalability schemes in real-time SHVC coding.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
PublisherIEEE
Pages1166-1170
Number of pages5
ISBN (Electronic)9781728163956
DOIs
Publication statusPublished - Oct 2020
Publication typeA4 Article in a conference publication
EventIEEE International Conference on Image Processing - Virtual, Abu Dhabi, United Arab Emirates
Duration: 25 Sep 202028 Sep 2020

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2020-October
ISSN (Print)1522-4880

Conference

ConferenceIEEE International Conference on Image Processing
Country/TerritoryUnited Arab Emirates
CityVirtual, Abu Dhabi
Period25/09/2028/09/20

Keywords

  • High Efficiency Video Coding (HEVC)
  • Kvazaar HEVC encoder
  • Scalable HEVC (SHVC)
  • signal-to-noise ratio (SNR) scalability
  • spatial scalability

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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