Development of New Image Fusion Techniques
Iqbal Ch, M Munawwar
creator
Supervised by Dr. Naima Iltaf
text
Rawalpindi
MCS (NUST)
2020
monographic
xv, 108 p
The imagefusionprocessaimstocombinethecrucialinformationfrommultipleim-
ages obtainedfromdifferentresources.Numerousimagefusiontechniquesarepro-
posed toachievebetterfusionaccuracyhowevertheygenerallyyieldlessinformative
edge details,introduceartifactsandhaveblurreddetailsinmultifocusimages.More-
over,inmedicalimages,resultantfusedimageshavemissingfinedetailsofdifferent
tissues, improperfusionofdifferenttissuesandboundariesarealsonotclearlydemar-
cated.
This workpresents,differentmulti-focusandmulti-modeltechniquestominimize
the above-mentionedissues/limitation.Crossbilateralfilterwhichprovidesbetterper-
ceptual qualityiscombinedwithnon-subsampledcontourlettransformtomaximize
the usefulinformationpresentinmultiplescalesanddirections.Guidedfilterwhose
computing timeisindependentoffiltersizeandwellpreservesedgesiscombinedwith
discrete wavelettransformformoreinformativeedgedetails.Alphamapalongwith
top hattransformextractscommonpropertiesofdifferentimages.Saliencymapshows
more meaningfulrepresentationofimagethereforeitisusedalongwithcrossbilat-
eral filtertofusemultimodalbrainimagemodalitieswhichhelptocombinethefacts
found inmultiplemedicalimagesthathaveexceptionaldistinctivemodalities.Energy
of Laplaciananddiscretewavelettransformbasedfusionofmultimodalbrainimages
helps toproperlydemarcateboundariesofdifferenttissues.Shiftinvariantdiscrete
wavelettransformandsparsefusionisusedformoreinformativeanatomydetailsof
medical imageswhichhelpsradiologistsinevaluatingdifferentmodalityimages.
Proposed multifocusimagefusionschemesmaintaindifferentimagedetailslikere-
duce edgeblurring,introducelessartifactsandpreservesharpedgedetails.Moreover,
suggested multimodalimagefusionschemesformedicalimagespreservethefinede-
tails ofdifferenttissues,properfusionofdifferenttissuesandclearlydemarcatethe
boundaries toobtainhighqualityfusedimage.Higherquantitativeandqualitativeout-
comes areobservedintheproposedframeworksforfusionschemesascomparedto
other existingschemes.
In generalourresearchworkpresentsmulti-focusandmulti-modelimagefusion
problems intwomaindomainsi.e.photographyapplications(toovercometheproblem
of depthoffieldofcameras)andbiomedicalimaging.Theproposednovelandeffec-
tivealgorithmshavebeentestedonrealworlddatatodemonstratetheirperformance
improvement.
M Munawwar Iqbal Ch
PhD Computer Software Engineering Thesis
PhD CSE Thesis
005.1,IQB