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Seeing Through Water
A.A. Efros, V. Isler, J. Shi, and M. Visontai
Neural >Information Processing Systems (NIPS 17), 2004.

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We consider the problem of recovering an underwater image distorted by surface waves. A large amount of video data of the distorted image is acquired. The problem is posed in terms of finding an undistorted image patch at each spatial location. This challenging reconstruction task can be formulated as a manifold learning problem, such that the center of the manifold is the image of the undistorted patch. To compute the center, we present a new technique to estimate global distances on the manifold. Our technique achieves robustness through convex flow computations and solves the “leakage” problem inherent in recent manifold embedding techniques.

Associated center: VASC

Number of pages: 8

A.A. Efros, V. Isler, J. Shi, and M. Visontai, "Seeing Through Water," Neural >Information Processing Systems (NIPS 17), 2004.

@inproceedings{Efros_2004_5238,
   author = "Alexei A. Efros and Volkan Isler and Jianbo Shi and Mirko Visontai",
   title = "Seeing Through Water",
   booktitle = "Neural >Information Processing Systems (NIPS 17)",
   year = "2004"
}