000			02813nam a22001697a 4500
003			NUST
082			_a005.1,IQB
100			_aIqbal Ch, M Munawwar _9124509
245			_aDevelopment of New Image Fusion Techniques / _cM Munawwar Iqbal Ch
260			_aRawalpindi, _bMCS (NUST), _c2020
300			_axv, 108 p
505			_aThe 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.
650			_aPhD Computer Software Engineering Thesis _9132801
651			_aPhD CSE Thesis _9132802
700			_aSupervised by Dr. Naima Iltaf _9132895
942			_2ddc _cTHE
999			_c615914 _d615914