Depth-based inpainting for disocclusion filling

Depth-based inpainting methods can solve disocclusion problems occurring in depth-image-based rendering. However, inpainting in this context suffers from artifacts along foreground objects due to foreground pixels in the patch matching. In this paper, we address the disocclusion problem by a refined depth-based inpainting method. The novelty is in classifying the foreground and background by using available local depth information. Thereby, the foreground information is excluded from both the source region and the target patch. In the proposed inpainting method, the local depth constraints imply inpainting only the background data and preserving the foreground object boundaries. The results from the proposed method are compared with those from the state-ofthe art inpainting methods. The experimental results demonstrate improved objective quality and a better visual quality along the object boundaries.