Tuning of Fuzzy Sharpening Filters for Biomedical Image Enhancement
Jaromir Kukal, Abduljalil Sireis, Zuzana Krbcova
Mendel · 2018
doi:10.13164/mendel.2018.1.121 (opens in a new tab)
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Abstract
Various 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.
Abstract licence: CC BY-NC-SA
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