Depth map upsampling using depth local features

Abstract

A depth map upsampling method using depth local features is proposed. Depth discontinuity and depth variance are extracted from a low-resolution depth map and a colour image as the depth local features. They are incorporated into an energy function for the Markov random field (MRF)-based depth upsampling. The high-resolution depth map is obtained by optimising the energy function using belief propagation. The experimental results show that the proposed method outperforms other depth upsampling approaches in terms of the bad pixel rate. © 2014 The Institution of Engineering and Technology.