Abstract
A big part of the video content we consume from video providers consists of genres featuring low-light aesthetics. Low light sequences have special characteristics, such as spatio-temporal varying acquisition noise and light flickering, that make the encoding process challenging. To deal with the spatio-temporal incoherent noise, higher bitrates are used to achieve high objective quality. Additionally, the quality assessment metrics and methods have not been designed, trained or tested for this type of content. This has inspired us to trigger research in that area and propose a Grand Challenge on encoding low-light video sequences. In this paper, we present an overview of the proposed challenge, and test state-of-the-art methods that will be part of the benchmark methods at the stage of the participants’ deliverable assessment. From this exploration, our results show that VVC already achieves a high performance compared to simply denoising the video source prior to encoding. Moreover, the quality of the video streams can be further improved by employing a post-processing image enhancement method.
Original language | English |
---|---|
Title of host publication | 2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW) |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Number of pages | 6 |
ISBN (Print) | 978-1-7281-1485-9/20 |
DOIs | |
Publication status | Published - 10 Jul 2020 |
Event | IEEE International Conference on Multimedia and Expo - London, United Kingdom Duration: 6 Jul 2020 → 10 Jul 2020 |
Conference
Conference | IEEE International Conference on Multimedia and Expo |
---|---|
Country/Territory | United Kingdom |
City | London |
Period | 6/07/20 → 10/07/20 |
Keywords
- data compression
- image denoising
- image enhancement
- image sequences
- video coding
- video signal processing
- video streaming
- VVC
- denoising
- quality metrics
- low light scenes
Fingerprint
Dive into the research topics of 'Encoding in the Dark Grand Challenge: An Overview'. Together they form a unique fingerprint.Equipment
-
HPC (High Performance Computing) and HTC (High Throughput Computing) Facilities
Sadaf R Alam (Manager), Steven A Chapman (Manager), Polly E Eccleston (Other), Simon H Atack (Other) & D A G Williams (Manager)
Facility/equipment: Facility