arXiv:1406.7444

Learning to Deblur

Christian J. Schuler, Michael Hirsch, Stefan Harmeling, Bernhard Schölkopf

제출 2014-06-28

원문 초록

We describe a learning-based approach to blind image deconvolution. It uses a deep layered architecture, parts of which are borrowed from recent work on neural network learning, and parts of which incorporate computations that are specific to image deconvolution. The system is trained end-to-end on a set of artificially generated training examples, enabling competitive performance in blind deconvolution, both with respect to quality and runtime.

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