Abstract
The visual quality is a critical factor in prediction video coding over packet-switched networks. However, the traditional MSE-based error resilient video coding cannot correlate well with the perceptual characteristics of the human visual system (HVS). This paper proposes a structural similarity (SSIM) based error resilient video coding scheme to improve the visual quality of compressed videos over packet-switched networks. In the proposed scheme, a SSIM-based end-to-end distortion model is developed to estimate the perceptual distortion due to quantization, error concealment, and error propagation. Based on this model, an adaptive mode selection strategy is presented to enhance the communication robustness of compressed videos. Experiments show that the proposed scheme significantly improves the visual quality for H.264/AVC video coding over packet-switched networks.
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