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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F14%3A00222807%21RIV15-MSM-21230___
rdf:type
n16:Vysledek skos:Concept
dcterms:description
We propose a novel binarization method based on a signal reconstruction using an iterative detection network. The algorithm simulates the whole image acquisition process taking into account a point spread function of the imaging system and its noise characteristics. The negative influence of image blur and noise is effectively suppressed by iterative detection network based on the criterion of maximum a posteriori probability. The proposed method was successfully applied to noisy microscopy images. Experiments show that the proposed method due to the noise suppression and deconvolution properties provides for noisy images significantly better results compared to common thresholding techniques. Binarized images obtained by the proposed method can be particularly useful for particle detection and analysis of cell samples. We propose a novel binarization method based on a signal reconstruction using an iterative detection network. The algorithm simulates the whole image acquisition process taking into account a point spread function of the imaging system and its noise characteristics. The negative influence of image blur and noise is effectively suppressed by iterative detection network based on the criterion of maximum a posteriori probability. The proposed method was successfully applied to noisy microscopy images. Experiments show that the proposed method due to the noise suppression and deconvolution properties provides for noisy images significantly better results compared to common thresholding techniques. Binarized images obtained by the proposed method can be particularly useful for particle detection and analysis of cell samples.
dcterms:title
Binarization of noisy microscopy images through signal reconstruction using iterative detection network Binarization of noisy microscopy images through signal reconstruction using iterative detection network
skos:prefLabel
Binarization of noisy microscopy images through signal reconstruction using iterative detection network Binarization of noisy microscopy images through signal reconstruction using iterative detection network
skos:notation
RIV/68407700:21230/14:00222807!RIV15-MSM-21230___
n3:aktivita
n8:S n8:P
n3:aktivity
P(GAP102/10/1320), P(LD12018), S
n3:dodaniDat
n9:2015
n3:domaciTvurceVysledku
n4:1605046 n4:4132920 n4:8983763 n4:9596755
n3:druhVysledku
n15:D
n3:duvernostUdaju
n21:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
5277
n3:idVysledku
RIV/68407700:21230/14:00222807
n3:jazykVysledku
n14:eng
n3:klicovaSlova
Binarization; Microscopy Images; Image Processing; Image Reconstruction; Iterative Detection Network
n3:klicoveSlovo
n5:Image%20Processing n5:Iterative%20Detection%20Network n5:Binarization n5:Microscopy%20Images n5:Image%20Reconstruction
n3:kontrolniKodProRIV
[C1153731B7F4]
n3:mistoKonaniAkce
Paríž
n3:mistoVydani
Piscataway
n3:nazevZdroje
2014 IEEE International Conference on Image Processing (ICIP 2014)
n3:obor
n7:JA
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n6:GAP102%2F10%2F1320 n6:LD12018
n3:rokUplatneniVysledku
n9:2014
n3:tvurceVysledku
Klíma, Miloš Lukeš, Tomáš Fliegel, Karel Kekrt, Daniel
n3:typAkce
n18:WRD
n3:zahajeniAkce
2014-10-27+01:00
s:numberOfPages
4
n11:hasPublisher
IEEE
n20:isbn
978-1-4799-5750-7
n10:organizacniJednotka
21230