Cross Depth Image Filter-Based Natural Image Matting
Yujie Li, Huimin Lu, Lifeng Zhang, Seiichi Serikawa · 2013
In this paper we propose a novel explicit image filter called guided depth image filter for natural image matting. Different from the traditional matting model, the guided image filter computes the filtering output by considering the content of a depth image. The guided depth image filter can be used as an edge-preserving smoothing operator like bilateral filter, but has better behaviors near edges. The proposed filter by using nonlocal neighborhoods, and contribute a simple and fast algorithm giving competitive results. Experimental results indicate that our matting results are comparable to the state of the art methods.