02813nam a22001697a 4500 NUST 005.1,IQB Iqbal Ch, M Munawwar 124509 Development of New Image Fusion Techniques / M Munawwar Iqbal Ch Rawalpindi, MCS (NUST), 2020 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. PhD Computer Software Engineering Thesis 132801 PhD CSE Thesis 132802 Supervised by Dr. Naima Iltaf 132895 ddc THE 615914 615914 0 0 ddc 0 0 MCS MCS THE 2026-01-26 0 005.1,IQB MCSPhD CSE-12 2026-01-26 2026-01-26 THE Almirah No.68, Shelf No.5