No-reference pixel based video quality assessment for HEVC decoded video.

No-reference pixel based codec analysis of HEVC videos.No-reference pixel based estimation of the quantization parameter and PSNR for HEVC videos.No-reference pixel based video quality assessment of HEVC videos.Mapping from the feature space to a quality score using elastic net.Performance measured with content-independent cross-validation and across datasets. 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 4K UHD (resolution equal to 38402160) 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.