Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/5259
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dc.contributor.authorLindblad J.en
dc.contributor.authorSladoje N.en
dc.contributor.authorSuveer A.en
dc.contributor.authorDragomir A.en
dc.contributor.authorSintorn I.en
dc.date.accessioned2019-09-30T08:46:48Z-
dc.date.available2019-09-30T08:46:48Z-
dc.date.issued2015-12-28en
dc.identifier.isbn9781479986354en
dc.identifier.urihttps://open.uns.ac.rs/handle/123456789/5259-
dc.description.abstract© 2015 IEEE. We present a method which utilizes advantages of fuzzy object representations and image processing techniques adjusted to them, to further increase efficient utilization of image information. Starting from a number of low-resolution images of affine transformations of an object, we create its suitably defuzzified high-resolution reconstruction. We evaluate the proposed method on synthetic data, observing its performance w.r.t. noise sensitivity, influence of the number of used low-resolution images, sensitivity to object variation and to inaccurate registration. Our aim is to explore applicability of the method to real image data acquired by Transmission Electron Microscopy, in a biomedical application we are currently working on.en
dc.relation.ispartof5th International Conference on Image Processing, Theory, Tools and Applications 2015, IPTA 2015en
dc.titleHigh-resolution reconstruction by feature distance minimization from multiple views of an objecten
dc.typeConference Paperen
dc.identifier.doi10.1109/IPTA.2015.7367090en
dc.identifier.scopus2-s2.0-84963800459en
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/84963800459en
dc.relation.lastpage34en
dc.relation.firstpage29en
item.grantfulltextnone-
item.fulltextNo Fulltext-
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