Modelling of spatio–temporal interaction for video quality assessment

• Published in: Signal processing. Image communication 2010-08, Vol.25 (7), p.535-546
• Main Authors: Huynh-Thu, Quan, Ghanbari, Mohammed
• Format: Article
• Language: English
• Subjects: Artefacts; IP (Internet Protocol); Mathematical models; Networks; Objective model; Perception; Quality assessment; Spatial quality; Spatio–temporal interaction; Subjective quality; Temporal logic; Temporal quality; Video
• ISSN: 0923-5965; 1879-2677
• DOI: 10.1016/j.image.2010.03.006

Video services have appeared in the recent years due to advances in video coding and convergence to IP networks. As these emerging services mature, the ability to deliver adequate quality to end-users becomes increasingly important. However, the transmission of digital video over error-prone and bandwidth-limited networks may produce spatial and temporal visual distortions in the decoded video. Both types of impairments affect the perceived video quality. In this paper, we examine the impact of spatio–temporal artefacts in video and especially how both types of errors interact to affect the overall perceived video quality. We show that the impact of the spatial quality on overall video quality is dependent on the temporal quality and vice-versa. We observe that the introduction of a degradation in one modality affects the quality perception in the other modality, and this change is larger for high-quality conditions than for low-quality conditions. The contribution of the spatial quality to the overall quality is found to be greater than the contribution of the temporal quality. Our results also indicate that low-motion talking-head content can be more negatively affected by temporal frame freezing artefacts than other general type of content with higher motion. Based on the results of a subjective experiment, we propose an objective model to predict overall video quality by integrating the contributions of a spatial quality and a temporal quality. The non-linear model shows a very high linear correlation with subjective data.