A posteriori correction of camera characteristics from large image data sets

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Title: A posteriori correction of camera characteristics from large image data sets
Author(s): Afanasyev, P
Ravelli, RBG
Matadeen, R
De Carlo, S
Van Duinen, G
Alewijnse, B
Peters, PJ
Abrahams, J-P
Portugal, RV
Schatz, M
Van Heel, M
Item Type: Journal Article
Abstract: Large datasets are emerging in many fields of image processing including: electron microscopy, light microscopy, medical X-ray imaging, astronomy, etc. Novel computer-controlled instrumentation facilitates the collection of very large datasets containing thousands of individual digital images. In single-particle cryogenic electron microscopy (“cryo-EM”), for example, large datasets are required for achieving quasi-atomic resolution structures of biological complexes. Based on the collected data alone, large datasets allow us to precisely determine the statistical properties of the imaging sensor on a pixel-by-pixel basis, independent of any “a priori” normalization routinely applied to the raw image data during collection (“flat field correction”). Our straightforward “a posteriori” correction yields clean linear images as can be verified by Fourier Ring Correlation (FRC), illustrating the statistical independence of the corrected images over all spatial frequencies. The image sensor characteristics can also be measured continuously and used for correcting upcoming images.
Publication Date: 11-Jun-2015
Date of Acceptance: 31-Mar-2015
ISSN: 2045-2322
Publisher: Nature Publishing Group
Journal / Book Title: Scientific Reports
Volume: 5
Sponsor/Funder: Dutch Ministry of Economic Affairs
Biotechnology and Biological Sciences Research Council (BBSRC)
Funder's Grant Number: 2007200359
Copyright Statement: This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit
Keywords: Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
Publication Status: Published
Article Number: 10317
Appears in Collections:Faculty of Natural Sciences

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