Tuning of Fuzzy Sharpening Filters for Biomedical Image Enhancement

Simple item page
dc.contributor.authorKukal, Jaromir
dc.contributor.authorSireis, Abduljalil
dc.contributor.authorKrbcova, Zuzana
dc.coverage.issue1cs
dc.coverage.volume24cs
dc.date.accessioned2019-06-26T10:18:36Z
dc.date.available2019-06-26T10:18:36Z
dc.date.issued2018-06-01cs
dc.description.abstractVarious approaches are used for image smoothing and sharpening. The class of fuzzy filters is widely used in the case of spiky noise due to their non–linear behavior. A lot of popular fuzzy filters are realizable in Lukasiewicz algebra with square root. Frequently applied low-pass fuzzy filters were selected from literature and used for the image sharpening with dyadic weights. The first aim of the paper is to find the optimum sharpening with the best Signal–to–Noise Ratio criterion for various noise types and offer general suggestions for fuzzy filter selection. Our results are directly applicable to tomographic images from MRI, PET and SPECT scanners.en
dc.formattextcs
dc.format.extent121-128cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2018 vol. 24, č. 1, s. 121-128. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2018.1.121en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttp://hdl.handle.net/11012/179233
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/32cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 Internationa licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectimage smoothingen
dc.subjectimage sharpeningen
dc.subjectLukasiewicz algebraen
dc.subjectfuzzy image processingen
dc.subjectfilter banken
dc.subjectMRIen
dc.subjectPETen
dc.subjectSPECTen
dc.titleTuning of Fuzzy Sharpening Filters for Biomedical Image Enhancementen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
32-Article Text-75-1-10-20190218.pdf
Size:
609.13 KB
Format:
Adobe Portable Document Format
Description:
Download
Collections
Vol. 24, No. 1