【摘要】：橋梁的自動(dòng)解譯具有重要的應(yīng)用價(jià)值,而在影像分辨率為分米級(jí)、橋梁場(chǎng)景復(fù)雜、橋梁目標(biāo)較小的復(fù)雜情況下,準(zhǔn)確地進(jìn)行橋梁目標(biāo)的自動(dòng)識(shí)別比較困難。在分析高分辨率SAR(synthetic aperture radar)影像的統(tǒng)計(jì)特征和橋梁特征的基礎(chǔ)上,提出了一種新的橋梁自動(dòng)識(shí)別方法。首先采用基于Weibull分布的CFAR(constant false alarm rate)算法檢測(cè)出潛在橋梁目標(biāo),然后基于Wishart-H-Alpha分類和形態(tài)學(xué)處理提取出橋梁場(chǎng)景區(qū)域,隨后引入霍夫變換并利用橋梁的場(chǎng)景特征、幾何特征和散射特征識(shí)別出橋梁目標(biāo)。采用國(guó)產(chǎn)機(jī)載XSAR數(shù)據(jù)和美國(guó)AIRSAR數(shù)據(jù)進(jìn)行驗(yàn)證,結(jié)果表明,該識(shí)別方法在復(fù)雜情況下能夠取得令人滿意的識(shí)別結(jié)果,具有較好的適應(yīng)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(xué)測(cè)繪遙感信息工程國(guó)家重點(diǎn)實(shí)驗(yàn)室;武漢大學(xué)遙感信息工程學(xué)院;首都師范大學(xué)資源環(huán)境與旅游學(xué)院;
【基金】：測(cè)繪公益項(xiàng)目(201412002) 國(guó)家自然科學(xué)基金(91438203,61371199) 中國(guó)海事局煙臺(tái)溢油應(yīng)急技術(shù)中心項(xiàng)目 城市空間信息工程北京市重點(diǎn)實(shí)驗(yàn)室項(xiàng)目(2014204) 地理空間信息工程國(guó)家測(cè)繪地理信息局重點(diǎn)實(shí)驗(yàn)室項(xiàng)目(201406)~~
【分類號(hào)】：TP751;U446

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