Evaluation of No Reference Bitstream-based Video Quality Assessment Methods
This is an incremental review that helps researchers and practitioners in video processing by comparing existing models for quality assessment.
The paper reviewed nine parametric models for video quality assessment, evaluating their generalization on a dataset with realistic video sequences and subjective scores, and identified strengths and weaknesses of each model.
Many different parametric models for video quality assessment have been proposed in the past few years. This paper presents a review of nine recent models which cover a wide range of methodologies and have been validated for estimating video quality due to different degradation factors. Each model is briefly described with key algorithms and relevant parametric formulas. The generalization capability of each model to estimate video quality in real-application scenarios is evaluated and compared with other models, using a dataset created with video sequences from practical applications. These video sequences cover a wide range of possible realistic encoding parameters, labeled with mean opinion scores (MOS) via subjective test. The weakness and strength of each model are remarked. Finally, future work towards a more general parametric model that could apply for a wider range of applications is discussed.