On a variational theory of image amodal completion

We study a variational model for image amodal completion, i.e., the recovery of missing or damaged portions of a digital image by technics inspired by the well-known amodal completion process in human vision. Representing the image by a real-valued function and following an idea initially proposed in [32], our approach consists in finding a set of interpolating level lines which is optimal with respect to an appropriate criterion. We prove that this method is theoretically well-founded and we show the equivalence with a more classical approach based on a direct interpolation of the function.

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