TY  - BOOK
AU  - Iqbal Ch, M Munawwar
AU  - Supervised by Dr. Naima Iltaf
TI  - Development of New Image Fusion Techniques
U1  - 005.1,IQB 
PY  - 2020///
CY  - Rawalpindi
PB  - MCS (NUST)
KW  - PhD Computer Software Engineering Thesis
KW  - PhD CSE Thesis
N1  - 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
ER  -