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OALib Journal期刊
ISSN: 2333-9721
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基于马尔可夫随机场模型的sar图像积雪识别
DOI: 10.13232/j.cnki.jnju.2015.008, PP. 976-986
Keywords: 马尔可夫随机场,合成孔径雷达,图像分割,积雪识别,玛纳斯河流域
Abstract:
本文以新疆玛纳斯河流域2014年3月19日radasat-2影像为研究数据，采用马尔可夫随机场（markovrandomfield.mrf）模型分割方法进行积雪识别。mrf模型分割方法能够充分利用图像上下文信息，降低相干斑噪声对合成孔径雷达（syntheticapertureradar,sar数据的影响。通过初始k-means分割估算出mrf参数，建立先验模型和概率密度函数，利用迭代条件模式（iteratedconditional,icm）算法进行最大后验概率求解得到最优标记，从而识别出积雪。通过实测数据进行验证，该方法积雪识别精度达86.67%。结果表明：mrf模型分割方法的能够有效识别积雪；在地势较为平坦的地区，交叉极化hv方式下的后向散射系数与极化总功率span的识别效果较好；在地形起伏较大的地区，hv后向散射系数的识别效果随着高程和坡度的增加而降低，极化总功率span能够综合三种极化特征，较好地克服地形影响，提高积雪的识别精度。
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