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.