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1、偏振成像技術(shù)提取目標紋理的研究摘要本文主要通過實驗研究偏振圖像與強度圖像在目標探測方面上的優(yōu)劣。實驗基于偏振光特性結(jié)和Stokes矢量表示法,采用激光主動成像與自然光被動成像兩種方式,分別在室內(nèi)、外進行實驗,用CCD采集獲得各個目標3幅原始圖像,再用Matlab軟件對3幅原始圖像進行處理,得到多組距離、光強不同的偏振度圖像。獲得目標物體的強度圖像與偏振度圖像比較兩種圖像的優(yōu)劣。實驗結(jié)果表明:偏振圖像與強度圖像相比,偏振圖像對低照度(陰影等)部分、邊緣部分信息得到增強,偏振信息對物體的紋理探測效果明顯。所以偏振成像技術(shù)在軍事偵查、目標識別、海洋搜救等領(lǐng)域有廣闊應(yīng)用前景。關(guān)鍵
2、詞:偏振成像;斯托克斯矢量;圖像處理;偏振度圖像;強度圖AbstractThispaperthroughtheexperimentalstudyofpolarizationimageandimageintensityintargetdetectiononthemerits.ExperimentsbasedonpolarizedcharacteristicsandStokesvectorrepresentation,usinglaseractiveimagingwithnaturallightpassiveimagingintwoways,respectively,andi
3、ntheindoorexperiment,usingCCDdatafromeachtarget3pieceoftheoriginalimage,andthenMatlabsoftwareonthe3pieceoftheoriginalimageprocessing,resultinginmultiplesetsofdistance,intensityofdifferentdegreeofpolarizationimage.Toobtainthetargetobjectintensityimageanddegreeofpolarizationimagecomparisono
4、ftwoimagequality.Atthesametime,weuselinearpolarizationlaserasthelightsource,makingtargetdetectionandrecognitionexperimentforseveralconventionalman-madeobjectsandthenaturaltargetindoorandoutdoor.Weuseimageacquisitionsystemtogetstrengthimageandpolarizationimageofdifferentroughnessmetaltarge
5、tandnonmetallictargets,andwritingmatlabprogramtocalculategrayvaluesofimageandenhanceprocessing.Resultsshowthatinlinearpolarizationlaserirradiation,man-madeobjectsandthenaturaltargethaveverybigdifferenceinrefundpartialnature.Technologyoflinearpolarizationlaseractiveimagingcanimprovemetalta
6、rgetandbackgroundcontrasttothebenefitoftargetdetectionandrecognition.Inactiveimagingofpolarizedactiveimaging,smoothsurfacetargetsaremoreconducivetorecognize.Theexperimentalresultsshowthat:polarizationimageandstrengthcomparedtoimages,polarizationimageonlowintensity(shadowpart),edgeinformat
7、ionisenhanced,thepolarizationinformationofobjecttexturedetectioneffectisobvious.Sothepolarizationimagingtechnologyinmilitaryreconnaissance,targetidentification,marinesearchandrescueandotherfieldshavebroadapplicationprospects.Keywords:Polarizationimaging;Stokesvector