Understanding Blind Deconvolution Algorithms

By Anat Levin, Yair Weiss, Frédo Durand, William T. Freeman. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011

457 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Stochastic model-based minimization of weakly convex functions (2018, background): “This problem occurs in a number of fields, such as astronomy and computer vision [13, 39].”
Face Recognition Across Non-Uniform Motion Blur, Illumination, and Pose (2015, background): “However, it is space-variant blur that is encountered frequently in handheld cameras [4].”
Total Variation Blind Deconvolution: The Devil Is in the Details (2014, methodology): “[14] showed that any algorithm that tries to minimize that same energy would fail, as the desired solution has a higher energy than the no-blur solution, where the sharp image is the blurry input and the blur is a Dirac delta.”