测绘学报
測繪學報
측회학보
ACTA GEODAETICA ET CARTOGRAPHICA SINICA
2015年
1期
39-45
,共7页
交通遥感信息处理%车辆识别定位%Phong光照模型%阴影滤除%车窗干扰
交通遙感信息處理%車輛識彆定位%Phong光照模型%陰影濾除%車窗榦擾
교통요감신식처리%차량식별정위%Phong광조모형%음영려제%차창간우
traffic RS information processing%vehicle identification and location%phong illumination model%shadow suppress%windows interference
针对识别和定位路面上每辆汽车这一交通遥感图像处理的核心环节，提出一种解决方法。应用光照模型推导出路面、车辆（深浅两类）、汽车阴影在全色遥感影像中的亮度差异与亮度变化特征。以亮度差异为基础建立了能够将车辆区域从路面遥感图像中分割出来的图层分离算法。针对密集行驶的汽车因阴影相互覆盖而容易被误识别为一辆大型车的问题以及浅色车因深色车窗造成的识别结果割裂问题，利用亮度变化特征以及阴影、车窗与汽车的位置关系设计了车辆区域内的阴影和车窗干扰消除算法，通过闭运算实现了遥感图像中的汽车识别与定位。选用10幅交通遥感图像进行了测试，对浅色车的识别率大于92％，对深色车的识别率大于87％。
針對識彆和定位路麵上每輛汽車這一交通遙感圖像處理的覈心環節，提齣一種解決方法。應用光照模型推導齣路麵、車輛（深淺兩類）、汽車陰影在全色遙感影像中的亮度差異與亮度變化特徵。以亮度差異為基礎建立瞭能夠將車輛區域從路麵遙感圖像中分割齣來的圖層分離算法。針對密集行駛的汽車因陰影相互覆蓋而容易被誤識彆為一輛大型車的問題以及淺色車因深色車窗造成的識彆結果割裂問題，利用亮度變化特徵以及陰影、車窗與汽車的位置關繫設計瞭車輛區域內的陰影和車窗榦擾消除算法，通過閉運算實現瞭遙感圖像中的汽車識彆與定位。選用10幅交通遙感圖像進行瞭測試，對淺色車的識彆率大于92％，對深色車的識彆率大于87％。
침대식별화정위로면상매량기차저일교통요감도상처리적핵심배절，제출일충해결방법。응용광조모형추도출로면、차량（심천량류）、기차음영재전색요감영상중적량도차이여량도변화특정。이량도차이위기출건립료능구장차량구역종로면요감도상중분할출래적도층분리산법。침대밀집행사적기차인음영상호복개이용역피오식별위일량대형차적문제이급천색차인심색차창조성적식별결과할렬문제，이용량도변화특정이급음영、차창여기차적위치관계설계료차량구역내적음영화차창간우소제산법，통과폐운산실현료요감도상중적기차식별여정위。선용10폭교통요감도상진행료측시，대천색차적식별솔대우92％，대심색차적식별솔대우87％。
For the issue of vehicles recognition and location ,which is the key of traffic RS information processing ,an image processing method is presented .Based on the Phong model ,features of luminance difference and luminance variance of common objects ,including vehicles (dark and bright) and their shadows and road surface ,are extracted .By taking advantage of the features of luminance difference ,the vehicleregions,containing vehicle and its shadow,are extracted through layer separation firstly .And then ,in order to suppress interference caused by vehicle shadow which is easy to cause the connection between abreast running vehicles ,as well as suppress interference caused by vehicle window which might disturb the bright vehicle identification ,an algorithm is designed according to the features of luminance variance and the position relationship between vehicle and its shadow and window .Through morphological method ,the vehicles of different colors are extracted and located on the RS‐image .This method had been tested ,and more than 92% bright vehicles and 87% dark vehicles are detected .
