Visual comfort enhancement in stereoscopic 3D images using saliency-adaptive nonlinear disparity mapping

• Visual comfort enhancement in stereoscopic 3D images.
• Saliency-adaptive disparity maps to maintain the saliency influence.
• Nonlinear disparity mapping to minimize disparity distortion.
• Virtual view generation based on DIBR.
• Keeping the overall viewing image quality.

Perceptually salient regions have a significant effect on visual comfort in stereoscopic 3D (S3D) images. The conventional method of obtaining saliency maps is linear combination, which often weakens the saliency influence and distorts the original disparity range significantly. In this paper, we propose visual comfort enhancement in S3D images using saliency-adaptive nonlinear disparity mapping. First, we obtain saliency-adaptive disparity maps with visual sensitivity to maintain the disparity-based saliency influence. Then, we perform nonlinear disparity mapping based on a sigmoid function to minimize disparity distortions. Finally, we generate visually comfortable S3D images based on depth-image-based-rendering (DIBR). Experimental results demonstrate that the proposed method successfully improves visual comfort in S3D images by producing comfortable S3D images with high mean opinion score (MOS) while keeping the overall viewing image quality.