A novel texture-based asymmetric visibility threshold model for stereoscopic video coding

Asymmetric stereoscopic video coding is becoming increasingly popular, as it can reduce the bandwidth required for stereoscopic 3D delivery without degrading the visual quality. Based on the perceptual theory of binocular suppression, the left and right views of stereoscopic video are coded with different levels of quality. However, existing asymmetric perceptual coding approaches on stereoscopic video mainly focus on the threshold of whole image distortion. It is not so reasonable to use a single unified rather than adaptable perception threshold for a random natural stereoscopic image as the texture complexity typically varies in different blocks of image. In this paper, we generated an asymmetrically distorted stereoscopic image set with different texture densities and conducted a large number of subjective perceptual experiments. A strong correlation between the asymmetrical visibility threshold and texture complexity is revealed from the subjective experiments, and a texture-based asymmetrical visibility threshold model (TAVT) is established. Then, the model is extended to the hierarchical B picture (HBP) coding architecture and an asymmetric stereoscopic video coding method is proposed based on the TAVT model. Experimental results show that the proposed method can effectively reduce the unnecessary perceptual redundancy without visual quality degradation. Especially, it is more efficient for high bitrate configuration.