000848160 001__ 848160
000848160 005__ 20210129234006.0
000848160 037__ $$aFZJ-2018-03426
000848160 041__ $$aEnglish
000848160 1001_ $$0P:(DE-Juel1)169421$$aKleefeld, Andreas$$b0$$eCorresponding author$$ufzj
000848160 1112_ $$aSIAM Conference on Imaging Science 2018$$cBologna$$d2018-06-05 - 2018-06-08$$wItaly
000848160 245__ $$aMathematical morphology for multispectral images
000848160 260__ $$c2018
000848160 3367_ $$033$$2EndNote$$aConference Paper
000848160 3367_ $$2DataCite$$aOther
000848160 3367_ $$2BibTeX$$aINPROCEEDINGS
000848160 3367_ $$2DRIVER$$aconferenceObject
000848160 3367_ $$2ORCID$$aLECTURE_SPEECH
000848160 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1528796427_22830$$xAfter Call
000848160 520__ $$aThe processing of multispectral images is a challenging task due to the fact that the pixel content is vectorial and the definition of an order is difficult. A new geometrical framework based on double hypersimplices and the Loewner ordering is illustrated to define the two fundamental operations dilation and erosion for multispectral images. These are the two main building blocks of mathematical morphology to define higher morphological operations such as top hats, gradients, and the morphological Laplacian. Numerical results are given to show the advantages and shortcomings of the new proposed approach.
000848160 536__ $$0G:(DE-HGF)POF3-511$$a511 - Computational Science and Mathematical Methods (POF3-511)$$cPOF3-511$$fPOF III$$x0
000848160 909CO $$ooai:juser.fz-juelich.de:848160$$pVDB
000848160 9101_ $$0I:(DE-588b)5008462-8$$6P:(DE-Juel1)169421$$aForschungszentrum Jülich$$b0$$kFZJ
000848160 9131_ $$0G:(DE-HGF)POF3-511$$1G:(DE-HGF)POF3-510$$2G:(DE-HGF)POF3-500$$3G:(DE-HGF)POF3$$4G:(DE-HGF)POF$$aDE-HGF$$bKey Technologies$$lSupercomputing & Big Data$$vComputational Science and Mathematical Methods$$x0
000848160 9141_ $$y2018
000848160 920__ $$lno
000848160 9201_ $$0I:(DE-Juel1)JSC-20090406$$kJSC$$lJülich Supercomputing Center$$x0
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000848160 980__ $$aVDB
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