Comparing of Modern Methods Used to Assess the Quality of Video Sequences During Signal Streaming with and Without Human Perception

Nowadays there is a trend of streaming video taking up more and more of the bandwidth of the Internet. Evaluating the quality of compression is an important area of research. Modern information coding technologies imply a trade-off between resources and visual quality. Subjective video quality assessments are time-consuming to experiment with and impossible in real-time applications. Therefore, the interest in developing models for objective video quality estimation has a high growth trend in recent years. In this paper, we present an analysis of the current categories of objective quality metrics used to assess the quality of video sequences in streaming signal transmission. We also, present comparing of the performance of reduce-referenced metrics and full-reference metrics with metric, which correlates with human perception. This work will be useful for researchers in the field of video compression, and will also be useful for creating additional test materials, planning future experiments, and improving adaptive codecs.