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首页> 外文期刊>Geo-spatial information science >Log-cumulants of the finite mixture model and their application to statistical analysis of fully polarimetric UAVSAR data
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Log-cumulants of the finite mixture model and their application to statistical analysis of fully polarimetric UAVSAR data

机译：有限混合模型的对数累积量及其在全极化UAVSAR数据统计分析中的应用

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Since its first flight in 2007, the UAVSAR instrument of NASA has acquired a large number of fully Polarimetric SAR (PolSAR) data in very high spatial resolution. It is possible to observe small spatial features in this type of data, offering the opportunity to explore structures in the images. In general, the structured scenes would present multimodal or spiky histograms. The finite mixture model has great advantages in modeling data with irregular histograms. In this paper, a type of important statistics called log-cumulants, which could be used to design parameter estimator or goodness-of-fit tests, are derived for the finite mixture model. They are compared with log-cumulants of the texture models. The results are adopted to UAVSAR data analysis to determine which model is better for different land types.
机译：自2007年首次飞行以来，NASA的UAVSAR仪器已以非常高的空间分辨率获取了大量的全极化SAR（PolSAR）数据。可以在此类数据中观察较小的空间特征，从而有机会探索图像中的结构。通常，结构化场景将呈现多峰或尖峰直方图。有限混合模型在使用不规则直方图建模数据方面具有很大的优势。在本文中，为有限混合模型推导了一种重要的统计数据，称为对数累积量，可用于设计参数估计量或拟合优度检验。将它们与纹理模型的对数累积量进行比较。结果被用于UAVSAR数据分析，以确定哪种模型更适合不同的土地类型。

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