Improving HEVC Coding Efficiency Using Virtual Long-Term Reference Pictures
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Inter-frame prediction in HEVC uses two types of reference pictures: short-term and long-term. Out of these long-term reference (LTR) pictures enable exploiting correlation among frames with extended temporal distances. In addition, LTR pictures improve the inter-frame prediction where video scenes are repeated such as in TV-series episodes, news broad-casts and movies. In this context, this paper proposes an algorithm to calculate LTR pictures using artificially generated virtual reference frames for static-camera scenes. The experimental results demonstrate an average coding improvement of2.34%in terms of Bjøntegaard Delta Bit Rate(BDBR), when compared with the HEVC reference encoder HM16.8.
2020 IEEE 9th Global Conference on Consumer Electronics (GCCE 2020);
Erabadda, B., Mallikarachchi, T., Kulupana, G., Fernando, A. (2020) 'Improving HEVC Coding Efficiency Using Virtual Long-Term Reference Pictures', 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE 2020) Kobe: 13- 16th October 2020
Conference paper presented at 2020 IEEE 9th Global Conference on Consumer Electronics (GCCE 2020)
Cardiff Metropolitan University (Grant ID: Cardiff Metropolian (Internal))
This work was supported by the CONTENT4ALL project, which is funded under European Commission’s H2020 Framework Program (Grant number:762021).
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