Perceptual stereoscopic video coding using disparity just-noticeable-distortion model

In this paper, we propose perceptual stereoscopic video coding using a disparity just-noticeable-distortion (JND) model. We obtain the disparity JND model in stereo videos by disparity masking effects of the human visual system (HVS). The disparity JND model represents the maximum distortion of stereo perception that HVS cannot perceive. Based on the disparity JND model, we adjust prediction residuals to remove the perceptual redundancy of stereo videos. Thus, we achieve significant bit-rate saving while maintaining visual quality. Experimental results demonstrate that the proposed method significantly improves coding efficiency without loss of stereoscopic perceptual quality.