Abstract
This paper proposes a No-Reference (NR) Video
Quality Assessment (VQA) method for videos subject to the
distortion given by High Efficiency Video Coding (HEVC). The
proposed assessment can be performed either as a BitstreamBased
(BB) method or as a Pixel-Based (PB). It extracts or
estimates the transform coefficients, estimates the distortion, and
assesses the video quality. The proposed scheme generates VQA
features based on Intra coded frames, and then maps features
using an Elastic Net to predict subjective video quality. A set of
HEVC coded 4K UHD sequences are tested. Results show that
the quality scores computed by the proposed method are highly
correlated with the subjective assessment.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of IEEE International Conference on Visual Communication and Image Processing |
| Number of pages | 4 |
| Publisher | IEEE |
| Publication date | 2015 |
| Publication status | Published - 2015 |
| Event | 2015 IEEE Visual Communications and Image Processing - Nanyang Technological University, Singapore, Singapore Duration: 13 Dec 2015 → 16 Dec 2015 https://ieeexplore.ieee.org/xpl/conhome/7452873/proceeding |
Conference
| Conference | 2015 IEEE Visual Communications and Image Processing |
|---|---|
| Location | Nanyang Technological University |
| Country/Territory | Singapore |
| City | Singapore |
| Period | 13/12/2015 → 16/12/2015 |
| Internet address |
Keywords
- HEVC analysis
- No-Reference
- Video Quality Assessment
- Machine Learning
- Elastic Net
Fingerprint
Dive into the research topics of 'No-Reference Video Quality Assessment by HEVC Codec Analysis'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver