SSIM-Based End-to-End Distortion Model for Error Resilient Video Coding over Packet-Switched Networks

Lei Zhang, Qiang Peng, Xiao Wu

Abstract: Conventional end-to-end distortion models measure the overall distortion based on independent estimation of the source distortion and channel distortion. However, they are not correlating well with perceptual characteristics in which a strong dependency exists among the source distortion, channel distortion and video content. As most compressed videos are represented to human users, perception-based end-to-end distortion model should be developed for error resilient video coding. In this paper, we propose a SSIM-based end-to-end distortion model to optimally estimate the overall perceptual distortion due to quantization, error concealment and error propagation. Experiments show that the proposed end-to-end distortion model can bring significant visual quality improvement for H.264/AVC video coding over packet-switched networks.