PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Multiframe Blind Deconvolution, Super-Resolution, and Saturation Correction via Incremental EM
Stefan Harmeling, Suvrit Sra, Michael Hirsch and Bernhard Schölkopf
In: ICIP 2010, 26-29 Sep 2010, Hong Kong.


We formulate the multiframe blind deconvolution problem in an incremental expectation maximization (EM) framework. Beyond deconvolution, we show how to use the same framework to address: (i) super-resolution despite noise and unknown blurring; (ii) saturation-correction of overexposed pixels that confound image restoration. The abundance of data allows us to address both of these without using explicit image or blur priors. The end result is a simple but effective algorithm with no hyperparameters. We apply this algorithm to real-world images from astronomy and to super resolution tasks: for both, our algorithm yields increased resolution and deconvolved images simultaneously.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:7908
Deposited By:Stefan Harmeling
Deposited On:17 March 2011