Multichannel deblurring of digital images

Michal Šorel; Filip Šroubek; Jan Flusser

Kybernetika (2011)

  • Volume: 47, Issue: 3, page 439-454
  • ISSN: 0023-5954

Abstract

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Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of the methods.

How to cite

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Šorel, Michal, Šroubek, Filip, and Flusser, Jan. "Multichannel deblurring of digital images." Kybernetika 47.3 (2011): 439-454. <http://eudml.org/doc/197088>.

@article{Šorel2011,
abstract = {Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of the methods.},
author = {Šorel, Michal, Šroubek, Filip, Flusser, Jan},
journal = {Kybernetika},
keywords = {image restoration; blind deconvolution; deblurring; spatially varying blur; image restoration; blind deconvolution; deblurring; spatially varying blur},
language = {eng},
number = {3},
pages = {439-454},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Multichannel deblurring of digital images},
url = {http://eudml.org/doc/197088},
volume = {47},
year = {2011},
}

TY - JOUR
AU - Šorel, Michal
AU - Šroubek, Filip
AU - Flusser, Jan
TI - Multichannel deblurring of digital images
JO - Kybernetika
PY - 2011
PB - Institute of Information Theory and Automation AS CR
VL - 47
IS - 3
SP - 439
EP - 454
AB - Blur is a common problem that limits the effective resolution of many imaging systems. In this article, we give a general overview of methods that can be used to reduce the blur. This includes the classical multi-channel deconvolution problems as well as challenging extensions to spatially varying blur. The proposed methods are formulated as energy minimization problems with specific regularization terms on images and blurs. Experiments on real data illustrate very good and stable performance of the methods.
LA - eng
KW - image restoration; blind deconvolution; deblurring; spatially varying blur; image restoration; blind deconvolution; deblurring; spatially varying blur
UR - http://eudml.org/doc/197088
ER -

References

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