Occlusion-aware light field depth estimation usingside window angular coherence
2020
Depth estimation is crucial in many light field applications.
However, the accuracy of light field depth estimation is prone to be
affected by occlusions. In this paper, a method of side window angular
coherence is proposed to handle different types of occlusions, and the
ability of the proposed method to resist occlusions is theoretically
analyzed. The angular patch is divided into several discrete side window
subsets. These subsets are a pure occluder-type subset, a pure object
point–type subset, and a hybrid-type subset. The photo-consistency of the
pure object point–type subset can reflect the true depth. Meanwhile, the
occlusion edges can be detected to identify occluded points and
nonoccluded points so the robustness of the algorithm can be further
enhanced by processing the two types of points. Moreover, fast guided
filtering is applied to cost volume for improving the accuracy of depth
estimation. Experimental results demonstrate that our method outperforms
the state-of-the-art depth estimation methods on both synthetic and real
scenes, especially near occlusion boundaries.
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