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Variational Depth From Focus Reconstruction
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DOI：10.1109/TIP.2015.2479469.png)
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摘要
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This paper deals with the problem of reconstructing a depth map from a sequence of differently focused images, also known as depth from focus (DFF) or shape from focus. We propose to state the DFF problem as a variational problem, including a smooth but nonconvex data fidelity term and a convex nonsmooth regularization, which makes the method robust to noise and leads to more realistic depth maps. In addition, we propose to solve the nonconvex minimization problem with a linearized alternating directions method of multipliers, allowing to minimize the energy very efficiently. A numerical comparison to classical methods on simulated as well as on real data is presented.
Keyword:
Depth from focus
depth estimation
nonlinear variational methods
alternating directions method of multipliers
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
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