简介:高压缩比率,高译码性能,和进步数据传播是为WebGIS的向量数据压缩算法的最重要的要求。满足这些要求,我们在场一条新压缩途径。这篇论文由把漂流坐标变换成整数坐标以多尺度的数据的产生开始。在屏幕上的变换的点和原来的点之间的距离在2个象素以内,这被证明,因此,我们的途径对顾客方面上的向量数据的可视化合适。整数坐标被传递给一个整数小浪变压器,并且高周波的系数由变压器生产了被正规哈夫曼代码编码。河数据和道路数据上的试验性的结果表明建议途径的有效性:为河数据的压缩比率罐头活动范围10%和20%为道路数据分别地。我们断定更多的注意需要被付到在包含一些点的弯曲之间的关联。
简介:Hyperspectralimageprovidesabundantspectralinformationforremotediscriminationofsubtledifferencesingroundcovers.However,theincreasingspectraldimensions,aswellastheinformationredundancy,maketheanalysisandinterpretationofhyperspectralimagesachallenge.Featureextractionisaveryimportantstepforhyperspectralimageprocessing.Featureextractionmethodsaimatreducingthedimensionofdata,whilepreservingasmuchinformationaspossible.Particularly,nonlinearfeatureextractionmethods(e.g.kernelminimumnoisefraction(KMNF)transformation)havebeenreportedtobenefitmanyapplicationsofhyperspectralremotesensing,duetotheirgoodpreservationofhigh-orderstructuresoftheoriginaldata.However,conventionalKMNForitsextensionshavesomelimitationsonnoisefractionestimationduringthefeatureextraction,andthisleadstopoorperformancesforpost-applications.Thispaperproposesanovelnonlinearfeatureextractionmethodforhyperspectralimages.Insteadofestimatingnoisefractionbythenearestneighborhoodinformation(withinaslidingwindow),theproposedmethodexplorestheuseofimagesegmentation.Theapproachbenefitsbothnoisefractionestimationandinformationpreservation,andenablesasignificantimprovementforclassification.Experimentalresultsontworealhyperspectralimagesdemonstratetheefficiencyoftheproposedmethod.ComparedtoconventionalKMNF,theimprovementsofthemethodontwohyperspectralimageclassificationare8and11%.Thisnonlinearfeatureextractionmethodcanbealsoappliedtootherdisciplineswherehigh-dimensionaldataanalysisisrequired.
简介:AnimprovedtopographicdatabaseforKingGeorgeIsland,oneofthemostfrequentlyvisitedregionsinAntarctica,ispresented.AfirststepconsistedincombiningdatafromdifferentialGPSsurveysgainedduringtheaustralsummers1997~1998and1999~2000,withthecurrentcoastlinefromaSPOTsatelliteimagemosaic,topographicinformationfromexistingmapsandfromtheAntarcticDigitalDatabase.Fromthisdatasets,adigitalterrainmodel(DTM)wasgeneratedusingArc/InfoGIS.Inasecondstep,asatelliteimagemapatthescale1∶100000wasassembledfromcontourlinesderivedfromtheDTMandthesatellitemosaic.Alackofaccuratetopographicinformationintheeasternpartoftheislandwasidentified.AdditionaltopographicsurveyingorSARinterferometryshouldbeusedtoimprovethedataqualityinthatarea.TheGISintegrateddatabasewillbeindispensableforglaciologicalandclimatologicalstudiesandadministrativeandscientificpurposes.Infuture,theapplicationofGIStechniqueswillbemandatoryforenvironmentalimpactstudiesandenvironmentalmonitoringaswellasformanagementplansonKingGeorgeIsland.
简介:Thispapercalculatestheparametersofimagepositionandorientation,proposesamathematicalmodelandadoptsanewmethodwiththreestepsoftransformationsbasedonparallelrayprojection.Everystepofthemodelisstrict,andthemapfunctionofeachtransformationisthefirstorderpolynomialsandothersimplefunction.Thefinalcalculationoftheparametersisforthelinearequationswithgoodstatus.Asaresult,theproblemoftherelativityofimageparametercalculationissolvedcompletely.Someexperimentsarecarriedout.
简介:Weareinvolvedinanembarrassingsituationthatthelimitedcapa-bilityofautomatedfeatureextractionindigitalphotogrammetricsystemscannotsatisfytheincreasingneedsforrapidacquisitionofsemanticinformationforappli-cations.Facingthischallenge,anewtactic,Human-ComputerCollaborative(HCC)tactic,andacorrespondingnewmethod,Operator-ObjectDirected(OOD)method,areproposedforthedesignofasystemforfeatureextractionfromlargescaleaerialimages.Weholdthatinalmostalltechnicalcomplexsys-tems,fullautomationwillbeneithertechnicallyfeasiblenorsociallyacceptable.Thesystemshouldbedesignedtooptimizethroughthecooperativeoperationwithtwoagentsinthesystem:thehumanandthecomputer.
简介:质地分析经常在处理领域的图象被讨论,但是大多数方法在灰色级的图象或颜色图象以内是有限的,并且质地的现在的概念主要基于单身的乐队的灰色级的图象被定义。遥感图象的必要字符之一多维或甚至高度维,并且传统的质地概念不能为这些包含足够的信息。因此,一个合适的质地定义基于遥感想象,对追求必要,它是在这份报纸的第一讨论。这份报纸描述印射的模型光谱在用Markov随机的地(MRF)的二维的图象空格的向量,基于MRF,和分析建立multiband遥感图象的一个质地模型吉布斯的计算势能和吉布斯参数。进一步,这份报纸也分析传统的吉布斯模型的限制,比较喜欢避免参数的评价的一个新吉布斯模型,并且以后介绍为hyperspectral遥感图象的一个新质地分割算法。
简介:Theprocessingofnonlineardatawasoneofhottopicsinsurveyingandmappingfieldinrecentyears.Asaresult,manylinearmethodsandnonlinearmethodshavebeendeveloped.Butthemethodsforprocessinggeneralizednonlinearsurveyingandmappingdata,especiallyfordifferentdatatypesandincludingunknownparameterswithrandomornonrandom,areseldomnoticed.Anewalgorithmmodelispresentedinthispaperforprocessingnonlineardynamicmultiple-periodandmultiple-accuracydataderivedfromdeformationmonitoringnetwork.