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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F06%3A00120898%21RIV10-MSM-21230___
rdf:type
n11:Vysledek skos:Concept
dcterms:description
It is generally known that every astronomical image which was acquired by CCD sensor, have to be corrected by dark frame. The Dark frame is mapping the dark current of the CCD. May become that we don't have the dark frame image and we cannot directly to correct the astronomical images. This work deals with dark frame correction based on Bayesian estimator in the wavelet domain. The models of the marginal probability density function (PDF) of the wavelet coefficients of astronomical images and dark frame images based on generalized Laplacian is used by this estimator. The parameters of the models, which were mentioned above, were estimated by least square error method on set of the images from our image database.The correction of the astronomical images by dark frame is better than the Bayesian estimator, but further work will deal with more sophisticated Bayesian estimator with more robust statistical description of the images. It is generally known that every astronomical image which was acquired by CCD sensor, have to be corrected by dark frame. The Dark frame is mapping the dark current of the CCD. May become that we don't have the dark frame image and we cannot directly to correct the astronomical images. This work deals with dark frame correction based on Bayesian estimator in the wavelet domain. The models of the marginal probability density function (PDF) of the wavelet coefficients of astronomical images and dark frame images based on generalized Laplacian is used by this estimator. The parameters of the models, which were mentioned above, were estimated by least square error method on set of the images from our image database.The correction of the astronomical images by dark frame is better than the Bayesian estimator, but further work will deal with more sophisticated Bayesian estimator with more robust statistical description of the images.
dcterms:title
Dark Frame Correction Via Bayesian Estimator in the Wavelet Domain Dark Frame Correction Via Bayesian Estimator in the Wavelet Domain
skos:prefLabel
Dark Frame Correction Via Bayesian Estimator in the Wavelet Domain Dark Frame Correction Via Bayesian Estimator in the Wavelet Domain
skos:notation
RIV/68407700:21230/06:00120898!RIV10-MSM-21230___
n3:aktivita
n18:P n18:Z
n3:aktivity
P(GA102/05/2054), P(GD102/03/H109), Z(MSM6840770014)
n3:dodaniDat
n9:2010
n3:domaciTvurceVysledku
n17:8430578 n17:7204698
n3:druhVysledku
n8:D
n3:duvernostUdaju
n21:S
n3:entitaPredkladatele
n10:predkladatel
n3:idSjednocenehoVysledku
470434
n3:idVysledku
RIV/68407700:21230/06:00120898
n3:jazykVysledku
n7:eng
n3:klicovaSlova
dark frame correction; wavelet transform
n3:klicoveSlovo
n15:dark%20frame%20correction n15:wavelet%20transform
n3:kontrolniKodProRIV
[14C322758589]
n3:mistoKonaniAkce
Vancouver
n3:mistoVydani
Madison
n3:nazevZdroje
2006 IEEE International Symposium on Signal Processing and Information Technology
n3:obor
n4:JA
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n13:GA102%2F05%2F2054 n13:GD102%2F03%2FH109
n3:rokUplatneniVysledku
n9:2006
n3:tvurceVysledku
Švihlík, Jan Páta, Petr
n3:typAkce
n20:WRD
n3:zahajeniAkce
2006-08-27+02:00
n3:zamer
n16:MSM6840770014
s:numberOfPages
4
n12:hasPublisher
Omnipress
n19:isbn
978-0-7803-9753-8
n22:organizacniJednotka
21230