Journal article
No-reference pixel based video quality assessment for HEVC decoded video
This paper proposes a No-Reference (NR) Video Quality Assessment (VQA) method for videos subject to the distortion given by the High Efficiency Video Coding (HEVC) scheme. The assessment is performed without access to the bitstream. The proposed analysis is based on the transform coefficients estimated from the decoded video pixels, which is used to estimate the level of quantization.
The information from this analysis is exploited to assess the video quality. HEVC transform coefficients are modeled with a joint-Cauchy probability density function in the proposed method. To generate VQA features the quantization step used in the Intra coding is estimated. We map the obtained HEVC features using an Elastic Net to predict subjective video quality scores, Mean Opinion Scores (MOS).
The performance is verified on a dataset consisting of HEVC coded 4 K UHD (resolution equal to 3840 x 2160) video sequences at different bitrates and spanning a wide range of content. The results show that the quality scores computed by the proposed method are highly correlated with the mean subjective assessments. (C) 2017 Elsevier Inc.
All rights reserved.
| Language: | English |
|---|---|
| Year: | 2017 |
| Pages: | 173-184 |
| ISSN: | 10959076 and 10473203 |
| Types: | Journal article |
| DOI: | 10.1016/j.jvcir.2017.01.002 |
| ORCIDs: | Forchhammer, Søren |
COMPUTER Cauchy probability density functions Computer Vision and Pattern Recognition Decoding ENCODED VIDEO Elastic net Electrical and Electronic Engineering HEVC analysis High-efficiency video coding INFORMATION Learning systems Machine learning Mathematical transformations Media Technology No references No-reference Pixels Probability density function Quality control REFERENCE PSNR ESTIMATION STANDARD Signal Processing Subjective video quality Video quality assessment Video quality assessments (VQA) Video signal processing
