Super Resolution for Multiview Images Using Depth Information

Abstract

In stereoscopic and multiview video, binocular suppression theory states that the visual subjective quality of 3-D experience is not much affected by asymmetrical blurring of the individual views. Based on these studies, mixed-resolution frameworks applied for multiview systems offer great data-size reduction without incurring in significant quality degradation in 3-D video applications. However, it is interesting to recover high-frequency content of the blurred views, to reduce visual strain due to long-term exposure and to make the system suitable for free-viewpoint television. In this paper, we present a novel super-resolution technique, in which low-resolution views are enhanced with the aid of high-frequency content from neighboring full-resolution views, and the corresponding depth information for all views. Occlusions are handled by checking the consistency between views. Tests for synthetic and real image data in stereo and multiview cases are presented, and results show that significant objective quality gains can be achieved without any extra side information.