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

Darren Ramsook, Vibhoothi Vibhoothi, Anil Kokaram, Angeliki Katsenou, David R Bull

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Abstract

This work evaluates the effectiveness of modernvideo restoration methods, contrasting neural network-basedtechniques with traditional statistical algorithms to improveperceived video quality. Our analysis focused on three distinctmethods: VBM4D, CVEGAN, and Ramsook, assessing theirperformance using pairwise subjective assessments with a compressed baseline. Results indicate a significant disparity betweenobjective and subjective evaluations, with traditional methods likeVBM4D showing limited improvements in perceptual quality, asdemonstrated by a statistically non-significant increase in MeanOpinion-Score (MOS). In contrast, the neural-based methods,CVEGAN and Ramsook, showed statistically significant improvements in subjective video quality. The findings highlight thesuperior capability of neural approaches to enhance perceptualquality, suggesting that current objective metrics may not fullycapture quality as perceived by human observers. This studyalso contributes the results of the comparative analysis and thedataset to the research community.
Original languageEnglish
Publication statusPublished - 20 Jun 2024
Event16th International Conference on Quality of Multimedia Experience (QoMEX’24) - Karlshamn, Sweden
Duration: 18 Jun 202420 Jun 2024
https://qomex2024.itec.aau.at/

Conference

Conference16th International Conference on Quality of Multimedia Experience (QoMEX’24)
Country/TerritorySweden
CityKarlshamn
Period18/06/2420/06/24
Internet address

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