Abstract

Light field depth estimation is an essential part of manylight field applications. Numerous algorithms have been de-veloped using various light field characteristics. However,conventional methods fail when handling noisy scene withocclusion. To remedy this problem, we present a light fielddepth estimation method which is more robust to occlusionand less sensitive to noise. Novel data costs using angu-lar entropy metric and adaptive defocus response are intro-duced. Integration of both data costs improves the occlusionand noise invariant capability significantly. Cost volumefiltering and graph cut optimization are utilized to improve the accuracy of the depth map. Experimental results con-firm that the proposed method is robust and achieves high quality depth maps in various scenes. The proposed method outperforms the state-of-the-art light field depth estimation methods in qualitative and quantitative evaluation.