Experimental Approach to the Selection of the Components in the Minimum Noise Fraction
Experimental Approach to the Selection of the Components in the Minimum Noise Fraction
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DOI：
10.1109/tgrs.2008.2002953
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发表时间：
2009-01-01
影响因子：
8.2
通讯作者：
Santini, Federico
中科院分区：
文献类型：
--
作者：
Amato, Umberto;Cavalli, Rosa Maria;Santini, Federico
提出了一种选择最小噪声分量（MNF）主成分个数的实验方法，用于对机载或卫星图像传感器测量的图像进行处理。该方法是基于光谱在黑暗条件下的实验测量，从中可以估计噪声结构。为了反映典型的陆地条件和大气变化，基于红外和可见光多光谱成像光谱仪的真实图像，建立了一个有意义的合成无噪声图像数据集。为此，在一些公共库中选择了一个很好地代表模拟图像的光谱子集。通过将这些合成图像与估计的噪声耦合，可以得到MNF中最优的分量数。为了有一个客观的（完全数据驱动的）过程，提出了一些标准，并对结果进行了验证，以估计组件的数量，而不依赖于辅助数据。通过一些简化，使整个过程在计算上可行。并与一种最优构件数估计算法进行了比较。
An experimental method to select the number of principal components in minimum noise fraction (MNF) is proposed to process images measured by imagery sensors onboard aircraft or satellites. The method is based on an experimental measurement by spectrometers in dark conditions from which noise structure can be estimated. To represent typical land conditions and atmospheric variability, a significative data set of synthetic noise-free images based on real Multispectral Infrared and Visible Imaging Spectrometer images is built. To this purpose, a subset of spectra is selected within some public libraries that well represent the simulated images. By coupling these synthetic images and estimated noise, the optimal number of components in MNF can be obtained. In order to have an objective (fully data driven) procedure, some criteria are proposed, and the results are validated to estimate the number of components without relying on ancillary data. The whole procedure is made computationally feasible by some simplifications that are introduced. A comparison with a state-of-the-art algorithm for estimating the optimal number of components is also made.