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Proceedings Paper

Digital super-resolution microscopy using example-based algorithm
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Paper Abstract

We propose a super-resolution microscopy with a confocal optical setup and an example-based algorithm. The example-based super-resolution algorithm was performed by an example database which is constructed by learning a lot of sets of a high-resolution patch and a low-resolution patch. The high-resolution patch is a part of the high-resolution image of an object model expressed in a computer, and the low-resolution patch is calculated from the high-resolution patch in consideration with a spatial property of an optical microscope. In the reconstruction process, a low-resolution image observed by the confocal optical setup with an image sensor is converted to the super-resolved high-resolution image selected by a pattern matching method from the example database. We demonstrate the adequate selection of the patch size and the weighting superposition method performs the super resolution with a low signal-to noise ratio.

Paper Details

Date Published: 22 June 2015
PDF: 7 pages
Proc. SPIE 9525, Optical Measurement Systems for Industrial Inspection IX, 952504 (22 June 2015); doi: 10.1117/12.2184826
Show Author Affiliations
Shinji Ishikawa, Utsunomiya Univ. (Japan)
Yoshio Hayasaki, Utsunomiya Univ. (Japan)

Published in SPIE Proceedings Vol. 9525:
Optical Measurement Systems for Industrial Inspection IX
Peter Lehmann; Wolfgang Osten; Armando Albertazzi Gonçalves Jr., Editor(s)

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