An adaptive perceptual quantization algorithm based on block-level JND for video coding

Abstract

It has been widely demonstrated that integrating efficient perceptual measures into traditional video coding framework can improve subjective coding performance significantly. In this paper, we propose a novel block-level JND (just-noticeable-distortion) model, which has not only adjusted pixel-level JND thresholds with more block characteristics, but also integrated them into a blocklevel model. And the model has been applied for adaptive perceptual quantization for video coding. Experimental results show that our model can save bit rates up to 24.5% on average with negligible degradation of the perceptual quality.