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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F08%3A03150872%21RIV09-MSM-21230___
rdf:type
n17:Vysledek skos:Concept
dcterms:description
We consider the problem of image matching under the unknown statistical dependence of the signals, i.e. a signal in one image may correspond to one or more signals in the other image with different probabilities. This problem is widely known as multimodal image registration and is commonly solved by the maximization of the empirical mutual information between the images. The deformation is typically represented in a parametric form and optimization w.r.t. it is performed using gradient-based methods. In contrast, we represent the deformation as a field of discretized displacements and optimize w.r.t. it using pairwise Gibbs energy minimization technique. This has potential advantage of finding good solutions even for problems having many local minima. We consider the problem of image matching under the unknown statistical dependence of the signals, i.e. a signal in one image may correspond to one or more signals in the other image with different probabilities. This problem is widely known as multimodal image registration and is commonly solved by the maximization of the empirical mutual information between the images. The deformation is typically represented in a parametric form and optimization w.r.t. it is performed using gradient-based methods. In contrast, we represent the deformation as a field of discretized displacements and optimize w.r.t. it using pairwise Gibbs energy minimization technique. This has potential advantage of finding good solutions even for problems having many local minima. We consider the problem of image matching under the unknown statistical dependence of the signals, i.e. a signal in one image may correspond to one or more signals in the other image with different probabilities. This problem is widely known as multimodal image registration and is commonly solved by the maximization of the empirical mutual information between the images. The deformation is typically represented in a parametric form and optimization w.r.t. it is performed using gradient-based methods. In contrast, we represent the deformation as a field of discretized displacements and optimize w.r.t. it using pairwise Gibbs energy minimization technique. This has potential advantage of finding good solutions even for problems having many local minima.
dcterms:title
A Discrete Search Method for Multi-modal Non-Rigid Image Registration A Discrete Search Method for Multi-modal Non-Rigid Image Registration A Discrete Search Method for Multi-modal Non-Rigid Image Registration
skos:prefLabel
A Discrete Search Method for Multi-modal Non-Rigid Image Registration A Discrete Search Method for Multi-modal Non-Rigid Image Registration A Discrete Search Method for Multi-modal Non-Rigid Image Registration
skos:notation
RIV/68407700:21230/08:03150872!RIV09-MSM-21230___
n3:aktivita
n6:Z n6:P
n3:aktivity
P(7E08031), P(GA102/07/1317), Z(MSM6840770038)
n3:dodaniDat
n5:2009
n3:domaciTvurceVysledku
n7:9335927 n7:5324564 n7:3572471
n3:druhVysledku
n16:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
354163
n3:idVysledku
RIV/68407700:21230/08:03150872
n3:jazykVysledku
n14:eng
n3:klicovaSlova
MRF; energy; matching; mutual information; registration
n3:klicoveSlovo
n4:matching n4:energy n4:mutual%20information n4:MRF n4:registration
n3:kontrolniKodProRIV
[52AED2B2855F]
n3:mistoKonaniAkce
Anchorage, Alaska
n3:mistoVydani
Los Alamitos
n3:nazevZdroje
NORDIA 2008: Proceedings of the 2008 IEEE CVPR Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment
n3:obor
n8:JD
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n18:GA102%2F07%2F1317 n18:7E08031
n3:rokUplatneniVysledku
n5:2008
n3:tvurceVysledku
Garcia Arteaga, Juan David Shekhovtsov, Oleksandr Werner, Tomáš
n3:typAkce
n15:WRD
n3:wos
000260371900123
n3:zahajeniAkce
2008-07-27+02:00
n3:zamer
n21:MSM6840770038
s:issn
1063-6919
s:numberOfPages
6
n12:hasPublisher
IEEE Computer Society Press
n22:isbn
978-1-4244-2339-2
n10:organizacniJednotka
21230