基于CFAR的高分PolSAR影像橋梁自動識別方法
發(fā)布時間：2018-08-05 20:05
【摘要】：橋梁的自動解譯具有重要的應用價值,而在影像分辨率為分米級、橋梁場景復雜、橋梁目標較小的復雜情況下,準確地進行橋梁目標的自動識別比較困難。在分析高分辨率SAR(synthetic aperture radar)影像的統(tǒng)計特征和橋梁特征的基礎上,提出了一種新的橋梁自動識別方法。首先采用基于Weibull分布的CFAR(constant false alarm rate)算法檢測出潛在橋梁目標,然后基于Wishart-H-Alpha分類和形態(tài)學處理提取出橋梁場景區(qū)域,隨后引入霍夫變換并利用橋梁的場景特征、幾何特征和散射特征識別出橋梁目標。采用國產(chǎn)機載XSAR數(shù)據(jù)和美國AIRSAR數(shù)據(jù)進行驗證,結(jié)果表明,該識別方法在復雜情況下能夠取得令人滿意的識別結(jié)果,具有較好的適應性。
[Abstract]:The automatic interpretation of the bridge has important application value, but it is difficult to identify the bridge target accurately when the image resolution is decimeter, the scene of the bridge is complex and the target of the bridge is small. Based on the analysis of the statistical features and bridge features of high-resolution SAR (synthetic aperture radar) images, a new automatic bridge recognition method is proposed. Firstly, the potential bridge targets are detected by CFAR (constant false alarm rate) algorithm based on Weibull distribution, then the bridge scene regions are extracted based on Wishart-H-Alpha classification and morphological processing, and then the Hough transform is introduced and the bridge scene features are used. Geometric features and scattering features identify bridge targets. The domestic airborne XSAR data and the American AIRSAR data are used to verify the proposed method. The results show that the method can obtain satisfactory recognition results under complex conditions and has good adaptability.
【作者單位】： 武漢大學測繪遙感信息工程國家重點實驗室;武漢大學遙感信息工程學院;首都師范大學資源環(huán)境與旅游學院;
【基金】：測繪公益項目(201412002) 國家自然科學基金(91438203,61371199) 中國海事局煙臺溢油應急技術(shù)中心項目 城市空間信息工程北京市重點實驗室項目(2014204) 地理空間信息工程國家測繪地理信息局重點實驗室項目(201406)~~
【分類號】：TP751;U446
本文編號：2166874
[Abstract]:The automatic interpretation of the bridge has important application value, but it is difficult to identify the bridge target accurately when the image resolution is decimeter, the scene of the bridge is complex and the target of the bridge is small. Based on the analysis of the statistical features and bridge features of high-resolution SAR (synthetic aperture radar) images, a new automatic bridge recognition method is proposed. Firstly, the potential bridge targets are detected by CFAR (constant false alarm rate) algorithm based on Weibull distribution, then the bridge scene regions are extracted based on Wishart-H-Alpha classification and morphological processing, and then the Hough transform is introduced and the bridge scene features are used. Geometric features and scattering features identify bridge targets. The domestic airborne XSAR data and the American AIRSAR data are used to verify the proposed method. The results show that the method can obtain satisfactory recognition results under complex conditions and has good adaptability.
【作者單位】： 武漢大學測繪遙感信息工程國家重點實驗室;武漢大學遙感信息工程學院;首都師范大學資源環(huán)境與旅游學院;
【基金】：測繪公益項目(201412002) 國家自然科學基金(91438203,61371199) 中國海事局煙臺溢油應急技術(shù)中心項目 城市空間信息工程北京市重點實驗室項目(2014204) 地理空間信息工程國家測繪地理信息局重點實驗室項目(201406)~~
【分類號】：TP751;U446
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