Fast MRF-Based Hole Filling for View Synthesis

Hole filling is one of the key issues in generating virtual view from video-plus-depth sequence by depth-image-based rendering. Hole filling method based on Markov random fields (MRF) is a practical way for view synthesis, but the traditional ones might introduce some foreground textures to the hole regions, and suffer from high computational complexity. In this letter, a fast MRF-based hole filling method is proposed for view synthesis, which is formulated as an energy minimization problem and is solved with loopy belief propagation (LBP). The energy function is optimized by employing the depth information to prevent the foreground textures filling holes. Furthermore, the LBP process maintains the visual consistency in the synthesized view by reserving all useful candidate labels. In addition, efficient belief propagation strategy is developed to optimize the LBP process, whose computational complexity is reduced to be linear with the number of candidate labels. Experimental results demonstrate the effectiveness of the proposed method with low running time and good visual consistency.