Asymmetric coding using Binocular Just Noticeable Difference and depth information for stereoscopic 3D
The problem of determining the best level of asymmetry has been addressed by several recent works with the aim to guarantee an optimal binocular perception while keeping the minimum required information. To do so, subjective experiments have been conducted for the definition of an appropriate threshold. However, such an approach is lacking in terms of generalization because of the content variability. Moreover, using a fixed threshold does not allow an adaptation to the content and to the images' quality. The traditional asymmetric stereoscopic coding methods apply a uniform asymmetry by considering that all regions of an image have the same perceptual relevance which is not in compliance with the characteristics of human visual system (HVS). Consequently, this paper describes a fully automated model that dynamically determines the best bounds of asymmetry for each region of the image. Based on the Binocular Just Noticeable Difference (BJND) and the depth level in the scene, the proposed method achieves non-uniform reduction of spatial resolution of one view of the stereo pair with the aim to reduce bandwidth requirement. Experimental results show that the proposed method results in up to 43% of bitrate saving while outperforming the widely used asymmetric coding approaches in terms of 3D visual quality.