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时间:2020-04-17
《用于高光谱图像分类的归一化光谱指数的构建与应用-论文.pdf》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、第43卷第2期红外与激光工程2014年2月Vo1.43No.2InfraredandLaserEngineeringFeb.2014DevelopmentandapplicationofnormalizedspectralindexbasedonhyperspectralimageryclassificationZhangDongyan,ZhaoJinling一,HuangLinsheng一,MaWenqiu。(1.KeyLaboratoryofIntelligentComputing&SignalProcessin
2、g,MinistryofEducation,Hefei230039,China2.BeijingResearchCenterforInformationTechnologyinAgriculture,Beijing100097,China)Abstract:Near——groundimagingspectroscopyappliedinfieldprovidesnewopportunityfordevelopmentofquantitativeremotesensinginagriculture.Itdeserves
3、concemabouthowtoexertitsdataadvantageofintegratingimageandspectraintoone,particularlyinanalyzingtheinfluenceofbackgroundtargets,suchassoil,shadowoncropnutrientinversionmode1.Inthisresearch,imagingcubesofwheatgroupinthefieldwerecollectedbyvisible/near-infraredim
4、agingspectrometer(VNIS).Anormalizedspectralindexwassetupaccordingtoreflectancecharacteristicsofilluminatedsoil,shadowsoil,illuminatedleafandshadowleafintheimage.Furthermore,theindexwasusedtoextractspectraofdifferenttargetsinsoybeanimagesandanalyzethevariationof
5、determinationcoeficientRbetweennormalizedspectraofsoybeangroupandchlorophylldensitybeforeandafterremovingbackgroundsoil.Theresultsshowedthatwhenspectraofsoilandshadowleafwereremoved,thesensitivebandsofchlorophylldensityshiftedfromredandnear—infraredranges(727nm
6、,922nm)toredranges(710nm,711nm),meanwhile,theoveralltrendwasthatvisiblerangesincreased,near-infraredregionsdecreasedandredbandshadthehighestdeterminationcoeficient.Therefore,itcanbeconcludedthatspectralpurificationbasedonnormalizedspectralindexhasimportantsigni
7、ficanceforquantitativeresearchinagriculturalremotesensing.Keywords:hyperspectralimaging;normalizedspectralindex;imageryclassification;spectrumpurification;wheat;soybeanCLCnumber:S127Documentcode:AArticleID:1007—2276(2014)02—0586—09用于高光谱图像分类的归一化光谱指数的构建与应用张东彦1,2,
8、赵晋陵1,2,黄林生1,2,马雯蔌(1.安徽大学智能计算与信号处理教育部重点实验室,安徽合肥230039;2.北京农业信息技术研究中心,北京100097)摘要:成像高光谱的近地田间应用为农业定量遥感的发展提供了新的契机。如何发挥其图谱合一的数据优势,尤其在解析土壤、阴影等背景地物对作物养分反演模型的影响需要关注。该研究借助可见/近红外收稿日期:
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