Adjacent Image Correlation for Video Quality Assessment
The main aim of this paper is to analyse correlation between adjacent images in a video sequence. Adjacent images with a slow or fast changeable scene in a video have high correlation which shows consistency in the video sequence therefore it can be the proof of normal reproduction of video service. Due to QoS (Quality of service) problems, especially over lossy network, appearance of different visual degradations in frames (images) during delivery of video service to end users can happen very often. In that case, adjacent images in the video sequence have low correlation which can be used as an indicator the problem occurred in some part of the network. In addition, the paper analyses correlation correspondent to polygons i.e. parts of adjacent images in the video sequence in order to discover a degree of influence visual degradations to user’s QoE (Quality of Experience). In order to check this aim, tested degraded and non-degraded video sequence was captured using IPTV system of one significant market power provider and processed in offline mod with Python script created especially for this purpose.