Quality assessment metrics vs. PSNR under packet lossscenarios in manet wireless networks

Abstract

It is well known that PSNR does not always rank quality of an image or video sequence in the same way that a human being. There are many other factors considered by the human visual system and the brain. So, a lot of efforts were required to find an objective video quality metric that is able to measure the quality distortion similarly to the one perceived by the destination user. We analyze the behaviour of some of the most relevant objective quality metrics when they are applied to video compressed by a H264/AVC codec at different bit-rates and with error resilience options enabled. Video data is transmitted in a wireless MANET environment and packet losses are modelled for different scenarios including variable congestion and mobility states. We take as reference the PSNR metric and try to find out if there is a more accurate metric in terms of human quality perception that could substitute PSNR in the performance evaluation of different coding proposals under packet loss scenarios.