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.

Abstract

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