Cluster based cross view filtering for compressed multi view depth maps
In the field of multi view video coding, multi view plus depth video is an important data format, but it always suffers from quantization errors, which result in obvious artifacts in consequent virtual view rendering. In this paper, we propose a cluster based cross view filtering (CBF) scheme for the enhancement of compressed depth maps. In this scheme, reconstructed depth information are mapped from cross view, and this information is benefit to the proposed filter. Then in filtering one viewpoint depth map with candidate information that are selected from non locally current and neighboring viewpoints. Specifically, in our scheme, candidates are clustered in 3D super pixel wise rather than block wise due to cross relationship among pixels in depth maps. The experimental results show that 2.0074 dB average gain can be obtained by our scheme, which suggests that the scheme outperforms than state of the art and classical filters in filtering the reconstructed depth maps.
2016 Visual Communications and Image Processing (VCIP)