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基于迭代多尺度引导滤波Retinex的低照度图像增强.docx

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基于迭代多尺度引导滤波Retinex的低照度图像增强 1.Introduction Inlow-lightconditions,imagesoftensufferfrompoorcontrast,lowluminance,andalackofdetails.Theseimagesarechallengingtointerpret,makingitdifficulttoextractusefulinformation.Thus,enhancinglow-lightimageshasbecomeacrucialtaskinvariousfields,includingmedicalimaging,surveillance,andforensicanalysis. Inthispaper,weproposeanovelmethodforlow-lightimageenhancementbasedoniterativemultiscaleguidedfilteringRetinex.TheRetinextheoryisbasedontheideathatanimageistheproductoftwofactors:reflectanceandillumination.Thereflectanceistheinherentpropertyofanobjectorscene,whileilluminationistheamountoflightthatilluminatestheobjectorscene.TheRetinextheoryaimstoseparatethesetwofactorstoachieveimageenhancement. 2.LiteratureReview Variousmethodshavebeenproposedforlow-lightimageenhancement,includinghistogramequalization,adaptivehistogramequalization,andcontraststretching.However,thesemethodsoftensufferfromissuessuchasover-enhancement,noiseamplification,andlossofcolorinformation.Toovercometheseissues,Retinex-basedmethodshavebeenproposed. TheRetinexalgorithmwasfirstproposedbyLandandMcCannin1971.Sincethen,variousRetinex-basedmethodshavebeenproposedforimageenhancement.Thesemethodsincludesingle-scaleRetinex,multiscaleRetinex,andguidedfilteringRetinex.Single-scaleRetinexusesafixed-scalekerneltoestimatethereflectanceandillumination.MultiscaleRetinexusesarangeofscalestoestimatereflectanceandilluminationatdifferentlevelsofdetail.GuidedfilteringRetinexusesaguidedimagetobetterpreserveedgesanddetailswhileenhancingtheimage. Recently,iterativemultiscaleguidedfilteringRetinexhasbeenproposedforlow-lightimageenhancement.Thismethodusesaniterativeapproachtoimprovetheaccuracyofthereflectanceandilluminationestimation.Italsousesguidedfilteringtobetterpreserveedgesanddetails. 3.ProposedMethod Ourproposedmethodforlow-lightimageenhancementisbasedoniterativemultiscaleguidedfilteringRetinex.Themainstepsoftheproposedmethodareasfollows: Step1:Imagedecompositionintoreflectanceandillumina