Guided depth filtering to improve the quality of experience for autostereoscopic displays

One of the drawbacks of current 3DTV systems are the glasses required to separate the 3D views. This problem can be solved by using autostereoscopic 3D displays, which generates a 3D scene from different viewpoints. These viewpoints are synthesized in the display based on depth information of the scene. However, currently no depth information is available for stereoscopic video. Therefore, depth estimation based on the stereoscopic input is required. This depth estimation should be low-complex and real-time for consumer electronic devices. Due to this low-complexity requirement, the quality of such depth maps will be limited. In this paper, we propose a guided depth filter, which filters the estimated depth map by using the downsampled chroma signal of the corresponding texture view as a guide. This allows to refine the borders of objects which reduces visible inpainting artifacts caused by the view synthesis. The proposed algorithm has been evaluated by expert viewing to show that it is independent of the depth map estimation and view synthesis of the autostereoscopic display