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Multiharmonic Postnonlinear Mixing Model for Hyperspectral Nonlinear Unmixing

机译:高光谱非线性解混的多谐波后非线性混和模型

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摘要

In this letter, a new method for higher order nonlinear hyperspectral unmixing is introduced. The proposed scheme relies on the harmonic description of the endmembers contributions to characterize the interactions among the materials showing up in the given scenes. Moreover, it aims at directly estimating the probability of occurrence of each material in the images, so to provide an accurate quantification of the endmembers also in complex scenarios. Experimental results carried out on synthetic and real data sets show that the proposed method is able to obtain good unmixing performance when compared to other state-of-the-art architectures.
机译:在这封信中,介绍了一种用于高阶非线性高光谱分解的新方法。提出的方案依赖于端构件贡献的谐波描述来表征给定场景中显示的材料之间的相互作用。而且,其目的在于直接估计图像中每种材料的出现概率,从而在复杂的情况下也提供端构件的准确量化。在合成和真实数据集上进行的实验结果表明,与其他最新体系结构相比,该方法能够获得良好的解混性能。

著录项

  • 来源
    《IEEE Geoscience and Remote Sensing Letters》 |2018年第11期|1765-1769|共5页
  • 作者单位

    Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China;

    Dipartimento di Ingegneria Industriale e dell’Informazione, Università degli Studi di Pavia, Pavia, Italy;

    Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China;

    Dipartimento di Ingegneria Industriale e dell’Informazione, Università degli Studi di Pavia, Pavia, Italy;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Hyperspectral imaging; Mixture models; Harmonic analysis; Earth; Sensors; Indexes;

    机译:高光谱成像;混合模型;谐波分析;地球;传感器;指标;

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