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A stable model-based three-component decomposition approach for polarimetric SAR data

机译:基于稳定模型的极化SAR数据三分量分解方法

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A stable model-based three-component decomposition approach for polarimetric SAR data is proposed in this paper. Two problems in the standard Freeman decomposition: (1) the instability of the decomposition; (2) the emergence of negative powers, have been stated. The proposed approach uses the regularization method to solve the problems, by minimizing a continuous objective function consisting two terms: (1) distance between the measured coherency matrix and the reconstructed one by the decomposition method; (2) the regularization term which implicates prior information. The AIRSAR polarimetric data acquired over San Francisco are decomposited by the proposed method. The results show that the stability is improved by the proposed decomposition approach and the negative powers are also eliminated by introducing constraints to the solution domain of decomposition.
机译:本文提出了一种基于稳定的基于模型的三组分分解方法,用于Polarimetric SAR数据。标准弗里曼分解中的两个问题:(1)分解的不稳定性; (2)已经说明了负权的出现。所提出的方法利用正则化方法来解决问题,通过最小化连续的目标函数,包括两个术语:(1)通过分解方法在测量的一致性矩阵和重建的一个之间的距离; (2)致命介绍事先信息的正则化术语。通过旧金山获取的航空偏振数据由所提出的方法分解。结果表明,通过提出的分解方法改善了稳定性,并且还通过向分解溶液结构域引入限制来消除负功率。

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