A spatiotemporal no-reference video quality assessment model

Abstract

Many researchers have been developing objective video quality assessment methods due to increasing demand for perceived video quality measurement results by end users to speed-up advancements of multimedia services. However, most of these methods are either Full-Reference (FR) metrics, which require the original video or Reduced-Reference (RR) metrics, which need some features extracted from the original video. No-Reference (NR) metrics, on the other hand, do not require any information about the original video; hence, are much more suitable for applications like video streaming. This paper presents a novel, objective, NR video quality assessment algorithm. The proposed algorithm is based on utilization of spatial extent of video, temporal extent of video using motion vectors, bit rate, and packet loss ratio. Test results obtained using LIVE video quality database demonstrate the accuracy and robustness of the proposed metric.