Polarimetric SAR Coherent Change Detection Method Based on Volume Scattering Constraint
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摘要: 相干变化检测(CCD)利用场景中变化区域的失相干特性进行检测，而场景中存在的体散射植被区域及低信噪比区域也呈现低相干特性，对待检测变化区域形成干扰。该文提出一种极化SAR CCD方法，首先利用变化前后SAR图像间的极化相干信息建立加权迹相干统计量，然后利用各个SAR图像内极化通道间的相干信息，通过建立混合GEV分布模型，采用改进EM算法求解各分量参数，建立体散射约束项，最后结合散射功率变化约束项构建极化CCD检验统计量。该方法可在不影响检测性能情况下排除干扰。该文采用变化前后的两幅L波段全极化SAR图像进行方法验证，实验结果及指标参数验证了该方法的正确性与有效性。Abstract: Coherent Change Detection (CCD) detects change areas in the scene using its decorrelation, yet vegetation areas with volume scattering and low signal-noise ratio areas in the scene also appear as low coherence, which causes interference to change areas to be detected. A polarimetric SAR CCD method is proposed. Firstly, the polarimetric coherence between two SAR images before and after changing is employed to set up weighted trace coherence statistics. Secondly, the polarimetric coherence between channels of each SAR image is employed to set up volume scattering constraint by establishing GEV mixture distribution model and solving parameters of each part using improved EM algorithm. Lastly, constraint of scattering power change is combined to set up the final polarimetric CCD test statistics. Using this method, the interference could be eliminated without influence of detect performance. The method is validated by two L-band full-polarimetric SAR images before and after changing. Results and index parameters demonstrate the correctness and validity of the proposed method.
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