Comparative Analysis of Subjective Evaluations for Traditional and Neural-Based Video Enhancement Techniques

This work evaluates the effectiveness of modern video restoration methods, contrasting neural network-based techniques with traditional statistical algorithms to improve perceived video quality. Our analysis focused on three distinct methods: VBM4D, CVEGAN, and Ramsook, assessing their performance using pairwise subjective assessments with a compressed baseline. Results indicate a significant disparity between objective and subjective evaluations, with traditional methods like VBM4D showing limited improvements in perceptual quality, as demonstrated by a statistically non-significant increase in Mean-Opinion-Score (MOS). In contrast, the neural-based methods, CVEGAN and Ramsook, showed statistically significant improvements in subjective video quality. The findings highlight the superior capability of neural approaches to enhance perceptual quality, suggesting that current objective metrics may not fully capture quality as perceived by human observers. This study also contributes the results of the comparative analysis and the dataset to the research community.