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Fast algorithm for spectral mixture analysis of imaging spectrometer data

机译:成像光谱仪数据光谱混合分析的快速算法

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Abstract: Imaging spectrometers acquire images in many narrow spectral bands but have limited spatial resolution. Spectral mixture analysis (SMA) is used to determine the fractions of the ground cover categories (the end-members) present in each pixel. In this paper a new iterative SMA method is presented and tested using a 30 band MAIS image. The time needed for each iteration is independent of the number of bands, thus the method can be used for spectrometers with a large number of bands. Further a new method, based on K-means clustering, for obtaining endmembers from image data is described and compared with existing methods. Using the developed methods the available MAIS image was analyzed using 2 to 6 endmembers. !16
机译:摘要:成像光谱仪可在许多狭窄的光谱带中采集图像,但空间分辨率有限。光谱混合分析(SMA)用于确定每个像素中存在的地面覆盖类别(端构件)的分数。本文提出了一种新的迭代SMA方法,并使用30波段MAIS图像进行了测试。每次迭代所需的时间与频带的数量无关,因此该方法可用于具有大量频带的光谱仪。进一步描述了一种基于K-means聚类的新方法,用于从图像数据中获取端成员,并将其与现有方法进行比较。使用开发的方法,使用2到6个末端成员分析了可用的MAIS图像。 !16

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