Detection of nonlinear mixtures using Gaussian processes: Application to hyperspectral imaging
Detection of nonlinear mixtures using Gaussian processes: Application to hyperspectral imaging
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使用高斯过程检测非线性混合物：在高光谱成像中的应用
DOI：
10.1109/icassp.2014.6855148
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
C. Richard
中科院分区：
文献类型：
--
作者：
T. Imbiriba;J. Bermudez;J. Tourneret;C. Richard
本文研究了利用高斯过程检测高光谱图像中的非线性混合像元。该方法不依赖于非线性混合机制，因此不受任何非线性混合模型的限制。所观察到的反射率估计使用最小二乘法和高斯过程。这两种方法的拟合误差结合在一个测试统计，它是可能的，以估计一个检测阈值给定所需的误报概率。所提出的检测器相比，最近提出的一个强大的非线性检测器使用合成数据，并示出提供更好的检测性能。新的检测器也测试了一个真实的高光谱图像。
This paper investigates the use of Gaussian processes to detect non-linearly mixed pixels in hyperspectral images. The proposed technique is independent of nonlinear mixing mechanism, and therefore is not restricted to any prescribed nonlinear mixing model. The observed reflectances are estimated using both the least squares method and a Gaussian process. The fitting errors of the two approaches are combined in a test statistics for which it is possible to estimate a detection threshold given a required probability of false alarm. The proposed detector is compared to a robust nonlinearity detector recently proposed using synthetic data and is shown to provide a better detection performance. The new detector is also tested on a real hyperspectral image.