HybridGeneticAlgorithmBasedImageEnhancementTechnologyAbstract:Inimageenhancement,TubbsproposedanormalizedincompleteBetafunctiontorepresentseveralkindsofcommonlyusednon-lineartransformfunctionstodotheresearchonimageenhancement.ButhowtodefinethecoefficientsoftheBetafunctionisstillaproblem.WeproposedaHybridGeneticAlgorithmwhichcombinestheDifferentialEvolutiontotheGeneticAlgorithmintheimageenhancementprocessandutilizethequicklysearchingabilityofthealgorithmtocarryouttheadaptivemutationandsearches.FinallyweusetheSimulationexperimenttoprovetheeffectivenessofthemethod.Keywords:Imageenhancement;HybridGeneticAlgorithm;adaptiveenhancementI.INTRODUCTIONIntheimageformation,transferorconversionprocess,duetootherobjectivefactorssuchassystemnoise,inadequateorexcessiveexposure,relativemotionandsotheimpactwillgettheimageoftenadifferencebetweentheoriginalimage(referredtoasdegradedordegraded)Degradedimageisusuallyblurredoraftertheextractionofinformationthroughthemachinetoreduceorevenwrong,itmusttakesomemeasuresforitsimprovement.Imageenhancementtechnologyisproposedinthissense,andthepurposeistoimprovetheimagequality.FuzzyImageEnhancementsituationaccordingtotheimageusingavarietyofspecialtechnicalhighlightssomeoftheinformationintheimage,reduceoreliminatetheirrelevantinformation,toemphasizetheimageofthewholeorthepurposeoflocalfeatures.Imageenhancementmethodisstillnounifiedtheory,imageenhancementtechniquescanbedividedintothreecategories:pointoperations,andspatialfrequencyenhancementmethodsEnhancementAct.Thispaperpresentsanautomaticadjustmentaccordingtotheimagecharacteristicsofadaptiveimageenhancementmethodthatcalledhybridgeneticalgorithm.Itcombinesthedifferentialevolutionalgorithmofadaptivesearchcapabilities,automaticallydeterminesthetransformationfunctionoftheparametervaluesinordertoachieveadaptiveimageenhancement.II.IMAGEENHANCEMENTTECHNOLOGYImageenhancementreferstosomefeaturesoftheimage,suchascontour,contrast,emphasisorhighlightedges,etc.,inordertofacilitatedetectionorfurth