학술논문

Comparative Rate-Distortion-Complexity Analysis of VVC and HEVC Video Codecs
Document Type
Periodical
Source
IEEE Access Access, IEEE. 9:67813-67828 2021
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Encoding
Complexity theory
Transforms
Decoding
Tools
Standards
Artificial intelligence
Common test conditions (CTC)
HEVC test model (HM)
high efficiency video coding (HEVC)
objective quality analysis
performance profiling
rate-distortion-complexity (RDC)
UVG dataset
versatile video coding (VVC)
video codec
VVC test model (VTM)
Language
ISSN
2169-3536
Abstract
Versatile Video Coding (VVC/H.266) is the next-generation international video coding standard and a successor to the widespread High Efficiency Video Coding (HEVC/H.265). This paper analyzes the rate-distortion-complexity characteristics of the VVC reference software (VTM10.0) by using HEVC reference software (HM16.22) as an anchor. In this independent study, the rate-distortion performance of VTM was benchmarked against HM with the objective PSNR, SSIM, and VMAF quality metrics and the associated encoder and decoder complexities were profiled at function level using Intel VTune Profiler on Intel Xeon E5-2699 v4 22-core processors. For a fair comparison, all our experiments were conducted under the VTM common test conditions (CTC) that define 10-bit configurations of the VTM codec for the addressed All Intra (AI), Random Access (RA), and Low Delay B (LB) conditions. The VTM CTC test set was also extended with complementary 4K UHD sequences to elaborate RD characteristics with higher resolutions. According to our evaluations, VTM improves the average coding efficiency over HM, depending on quality metric, by 23.0-23.9% under the AI condition, 33.1-36.6% under the RA condition, and 26.7-29.5% under the LB condition. However, the coding gain of VTM comes with $34.0\times $ , $8.8\times $ , and $7.5\times $ encoding complexity over that of HM under the AI, RA, and LB conditions, respectively. The corresponding overhead of the VTM decoder stays steady at $1.8\times $ across all conditions. This study also pinpoints the most complex parts of the VTM codec and discusses practical implementation aspects of prospective real-time VVC encoders and decoders.