Abstract:

The quality of the depth map is crucial for depth image based rendering (DIBR) which enables a variety of advanced 3D video related applications such as perceived depth adjustment for stereoscopic video and intermediate view generation for multiview auto-stereoscopic displays. However, the input depth map for DIBR may suffer from errors and noise, which could seriously impact the rendered view quality. In order to reduce the errors and suppress the noise in the depth map, a local depth image enhancement technique is proposed that leverages trellis-based optimization techniques. A cost function is used to evaluate candidate depth values based on the stereo cost as well as color and depth consistency. Sparse depth features are also used in the enhancement process. The experimental results show notable subjective improvements in terms of rendering quality.