Real-time 16K video coding on a GPU with complexity scalable BPC-PaCo

The advent of new technologies such as high dynamic range or 8K screens has enhanced the quality of digital images but it has also increased the codecs’ computational demands to process such data. This paper presents a video codec that, while providing the same coding features and performance as tho...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Signal processing. Image communication Ročník 99; s. 116503
Hlavní autoři: de Cea-Dominguez, Carlos, Moure, Juan C., Bartrina-Rapesta, Joan, Aulí-Llinàs, Francesc
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 01.11.2021
Elsevier BV
Témata:
Codec
Coding
Complexity
CUDA
Digital imaging
GPU
High throughput image and video coding
HTJ2K
Image enhancement
Image quality
JPEG2000
New technology
Real time
CUDA
JPEG2000
HTJ2K
High throughput image and video coding
GPU
ISSN:0923-5965, 1879-2677
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:The advent of new technologies such as high dynamic range or 8K screens has enhanced the quality of digital images but it has also increased the codecs’ computational demands to process such data. This paper presents a video codec that, while providing the same coding features and performance as those of JPEG2000, can process 16K video in real time using a consumer-grade GPU. This high throughput is achieved with a technique that introduces complexity scalability to a bitplane coding engine, which is the most computationally complex stage of the coding pipeline. The resulting codec can trade throughput for coding performance depending on the user’s needs. Experimental results suggest that our method can double the throughput achieved by CPU implementations of the recently approved High-Throughput JPEG2000 and by hardwired implementations of HEVC in a GPU.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0923-5965
1879-2677
DOI:10.1016/j.image.2021.116503