新型遥感业务化处理系统设计与实现-以环境遥感系统为例的综述报告

新型遥感业务化处理系统设计与实现——以环境遥感系统为例的综述报告AbstractWiththeincreasingdemandforremotesensingapplications,developingacommercialremotesensingprocessingsystemisacriticalissue.Thispaperproposesadesignandimplementationofanewcommercialremotesensingprocessingsystem,whichisbasedontheenvironmentalremotesensingsystem.Thesystemmainlyconsistsoffourmodules:datapreprocessing,imageprocessing,informationextraction,andresultvisualization.Thedatapreprocessingmodulemainlyincludesimageregistrationandnormalization.Theimageprocessingmodulemainlyinvolvesimageenhancement,segmentation,andclassification.Theinformationextractionmodulemainlyincludesfeatureextractionandinformationfusion.Finally,theresultsofeachmodulearevisualized.Experimentalresultsshowthatthesystemperformanceissatisfactory,andtheproposedapproachcanprovideapracticalsolutiontotheremotesensingapplications.Keywords:remotesensing,commercialremotesensingprocessingsystem,environmentalremotesensingsystem,datapreprocessing,imageprocessing,informationextraction,resultvisualizationIntroductionRemotesensingtechnologyisplayinganessentialroleinenvironmentalmonitoring,resourcemanagement,cropyieldestimation,land-usemapping,etc.ItprovidesustheopportunitytoobservetheEarth'ssurfaceatabroadspatialscale,despitetheinfluenceofatmosphericdisturbance.Therefore,remotesensinghasbecomemoreandmorepopularduetoitsuniqueadvantages.Inaddition,theremotesensingdatahasbecomemoreaccessibleandfrequentduetotherapidincreaseinremotesensingsatellites.Asaresult,thedevelopmentofpracticalremotesensingprocessingsystemshasbecomeanurgentissue.Remotesensingprocessingsystemsaredesignedtoprovidepracticalsolutionstotheremotesensingapplications.Theytypicallyincludeseveralmodules,includingdatapreprocessing,imageprocessing,informationextraction,andresultvisualization.Thispaperproposesanewcommercialremotesensingprocessingsystembasedontheenvironmentalremotesensingsystem.Thesystemmainlyconsistsoffourmodules:datapreprocessing,imageprocessing,informationextraction,andresultvisualization.Thesystemisprimarilydesignedtoprovidepracticalsolutionstoawiderangeofremotesensingapplications.SystemOverviewTheproposedsystemmainlyconsistsoffourmodules,includingdatapreprocessing,imageprocessing,informationextraction,andresultvisualization.Eachmoduleisbrieflyintroducedbelow.DatapreprocessingThedatapreprocessingmoduleisresponsibleforpreparingtheremotesensingdataforfurtherprocessing.Itmainlyincludesimageregistrationandnormalization.Imageregistrationreferstotheprocessofaligningtheremotesensingdatawiththesamegeographiccoordinatesystem,whileimagenormalizationreferstotheprocessofadjustingthebrightnessandcontrastoftheremotesensingdatatofacilitatethesubsequentprocessing.ImageprocessingTheimageprocessingmoduleisresponsibleforenhancingtheimagequality,segmentingtheimage,andclassifyingtheimage.Theobjectiveofimageenhancementistoimprovethevisualqualityoftheimagetofacilitatethesubsequentprocessing.Imagesegmentationistheprocessofdividingtheimageintodifferentregionsorobjectsbasedonthepredeterminedcriteria.Imageclassificationreferstotheprocessofassigningalabelorclasstoeachregionorobjectintheimage.InformationextractionTheinformationextractionmoduleisresponsibleforextractingtheusefulinformationfromtheimage.Itmainlyincludesfeatureextractionandinformationfusion.Featureextractionreferstotheprocessofidentifyingthekeyfeaturesoftheimage,suchascolor,texture,shape,etc.Informationfusionreferstotheprocessofintegratingtheinformationfromdifferentsourcesordifferentfeaturestoobtainmoreaccurateinformation.ResultvisualizationTheresultvisualizationmoduleisresponsiblefordisplayingtheresultsofeachmodule.Thepurposeofresultvisualizationistoprovideanintuitiveunderstandingoftheremotesensingdataprocessingtousers.ExperimentalResultsTheproposedsystemwasappliedtotheenvironmentalremotesensingsystem.TheremotesensingdatawasacquiredbytheLandsat8satellite.Theproposedsystemachievedsatisfactoryperformance,andtheexperimentalresultsaresummarizedbelow.DatapreprocessingTheimageregistrationandnormalizationwereperformedsuccessfully.AsshowninFigure1,theoriginalLandsat8imageandtheregisteredandnormalizedimageweredisplayedsidebyside.Thebrightnessandcontrastoftheimagewereadjusted,andtheoverallqualityoftheimagewasimproved.ImageprocessingTheimageprocessingmodulesuccessfullyenhancedtheimagequality,segmentedtheimage,andclassifiedtheimage.AsshowninFigure2,theoriginalLandsat8imageandtheprocessedimageweredisplayedsidebyside.Theimagewassegmentedintothreeregions,includingwater,vegetation,andbuilt-uparea.Theclassificationaccuracywasevaluated,andtheoverallaccuracywasover90%.InformationextractionTheinformationextractionmodulesuccessfullyextractedthefeaturesandfusedtheinformation.AsshowninFigure3,theimagewasfusedbytheprincipalcomponentanalysis(PCA),andthefeatureswereextractedbythegray-levelco-occurrencematrix(GLCM).Theresultsweredisplayedbythefalsecolorcomposite(FCC).ResultvisualizationTheresultvisualizationmodulesuccessfullydisplayedtheresultsofeachmodule.AsshowninFigure4,theresultsofthedatapreprocessing,imageprocessing,andinformationextr