arrow
Return

Low Complexity Quantization in High Efficiency Video Coding

delete2020-01-01
delete2
delete
OA
AI
M
Meng Wang
X
Xiaohan Fang
S
Songchao Tan *
X
Xinfeng Zhang
L
Li Zhang
DOI:10.1109/ACCESS.2020.3012145delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
The rate-distortion optimized quantization (RDOQ) provides an excellent trade-off between rate and distortion in High Efficiency Video Coding (HEVC), leading to inspiring improvement in terms of rate-distortion performance. However, its heavy use imposes high complexity on the encoder in real-world video compression applications. In this paper, we provide a comprehensive review on low complexity quantization techniques in HEVC, including both fast RDOQ and all-zero block detection. In particular, the fast RDOQ relies on rate and distortion models for rate-distortion cost estimation, such that the most appropriate quantized coefficient is selected in a low complexity way. All-zero block detection infers the all-zero block by skipping transform and quantization, in an effort to further reduce the complexity. The relationship between the two techniques is also discussed, and moreover, we also envision the future design of low complexity quantization in the upcoming Versatile Video Coding (VVC) standard.
Keywords:
Quantization (signal)
Video coding
Complexity theory
Transforms
Encoding
Rate-distortion
Standards
High efficiency video coding
low complexity video coding
rate-distortion optimized quantization
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

U
university of chinese academy of sciences, cas
Scholars:
4.1W
Papers: 3.8W
Citations: 75
C
City University of Hong Kong
Scholars:
2.3W
Papers: 3.0W
Citations: 6.1W
P
peking university
Scholars:
11.9W
Papers: 8.7W
Citations: 146
D
Dalian University of Technology
Scholars:
6.0W
Papers: 4.4W
Citations: 5.5W
C
chinese academy of sciences
Scholars:
56.7W
Papers: 45.0W
Citations: 704
researcher View more organizations
Cited Papers

Cited Papers

Spatiotemporal variance-guided filtering
err2017-07-28
err0
PREAI
errChristoph Schied; Anton Kaplanyan; Chris Wyman; Anjul Patney; Chakravarty R. Alla Chaitanya; John Burgess; Shiqiu Liu; Carsten Dachsbacher; Aaron Lefohn; Marco Salvi
errShare
errSave
An Improved Framework of Affine Motion Compensation in Video Coding
err2019-03-01
err58
PREAI
errZhang, Kai; Chen, Yi-Wen; Zhang, Li; Chien, Wei-Jung; Karczewicz, Marta
errShare
errSave
errShare
errSave
Toward Knowledge as a Service Over Networks: A Deep Learning Model Communication Paradigm
err2019-06-01
err17
PREAI
errChen, Ziqian; Duan, Ling-Yu; Wang, Shiqi; Lou, Yihang; Huang, Tiejun; Wu, Dapeng Oliver; Gao, Wen
errShare
errSave
1013-2007
err
IF0
err2007-01-01
err0
PREAI
err
errShare
errSave
researcher View more