Efficient Filter Flow for Space-Variant Multiframe Blind Deconvolution

Ultimately being motivated by facilitating space-variant blind deconvolution, we present a class of linear transformations, that are expressive enough for space-variant filters, but at the same time especially designed for efficient matrix-vector-multiplications. Successful results on astronomical imaging through atmospheric turbulences and on noisy magnetic resonance images of constantly moving objects demonstrate the practical significance of our approach.

• Type: Conference
• Year: 2010
• Where: CVPR
• Authors: Michael Hirsch, Suvrit Sra, Bernhard Schöpf, Stefan Harmeling
• Keywords: Computer Vision, CVPR 2010, Linear Transformations, Noisy Magnetic Resonance, Space-variant Blind Deconvolution