Improving HEVC Coding Efficiency Using Virtual Long-Term Reference Pictures
| Autor: | Buddhiprabha Erabadda, Anil Fernando, Thanuja Mallikarachchi, Gosala Kulupana |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Computer science
business.industry Context (language use) 02 engineering and technology Term (time) Algorithmic efficiency Bit rate 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Encoder Reference frame |
| Zdroj: | GCCE |
| DOI: | 10.1109/gcce50665.2020.9291917 |
| Popis: | 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 broadcasts 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 of 2.34% in terms of Bjontegaard Delta Bit Rate(BDBR), when compared with the HEVC reference encoder HM16.8. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|