The tutorial discusses an open and freely available encoder implementation VVenC of the latest video coding standard VVC (Versatile Video Coding) jointly developed by ITU-T and ISO/IEC. VVC has been designed to achieve significantly improved compression capability compared to previous standards such as HEVC, and at the same time to be highly versatile for effective use in a broadened range of applications.
Some key application areas for the use of VVC particularly include ultra-high-definition video (e.g. 4K or 8K resolution), video with a high dynamic range and wide color gamut (e.g., with transfer characteristics specified in Rec. ITU-R BT.2100), and video for immersive media applications such as 360° omnidirectional video, in addition to the applications that have commonly been addressed by prior video coding standards. Important design criteria for VVC have been low computational complexity on the decoder side and friendliness for parallelization on various algorithmic levels. VVC has been finalized in July 2020 and in September 2020. Fraunhofer HHI has made an optimized VVC software encoder (VVenC) and a VVC software decoder (VVdeC) implementations publicly available on GitHub.
The tutorial details the open encoder implementation VVenC with a specific focus on the challenges and opportunities in implementing the myriad of new coding tools. This includes algorithmic optimizations for specific coding tools such as block partitioning, motion estimation as well as implementation specific optimization such as SIMD vectorization and parallelization approaches. In addition to runtime optimizations, subjective quality measures and methods to increase the perceived quality by local QP adaptation are presented and discussed.
- The Versatile Video Coding Standard
- Introduction to VVC and short overview of tools
- VVC reference software (VTM) – general coding efficiency and runtime performance
- VVenC – general coding efficiency and runtime performance
- VVenC – Implementation and Algorithm Optimization
- VVC encoding complexity analysis
- Preset comparison and discussion
- Quad-tree plus binary- and ternary-tree partitioning complexity
- Tool complexity and configuration space analysis
- VVenC – Subjective Quality Optimizations
- Perceptually motivated block-wise distortion measures
- Perceptual QP adaptation based on PSNR and XPSNR
- Visual quality assessment (VQA) of image or video codecs via (MS-)SSIM, VMAF, and XPSNR
- Summary and outlook (5min)
Schedule: View the Agenda
- Benjamin Bross – Group Head (Video Coding Solutions)
- Dr.-Ing. Christian Helmrich – Research Associate
- Adam Wieckowski – Research Assistant