高光谱图像中鲁棒信号子空间识别算法:比较分析

2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Pub Date : 2009-10-16 DOI:10.1109/WHISPERS.2009.5288995

N. Acito, G. Corsini, M. Diani

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引用次数: 0

摘要

在这项工作中，我们提出了两种最近提出的算法在高光谱数据中的信号子空间识别(SSI)和降维(DR)的性能比较分析。这种SSI算法对稀有信号成分的存在具有鲁棒性，特别适用于在小目标检测应用中采用DR作为预处理步骤。

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Algorithms for robust signal subspace identification in hyperspectral images: A comparative analysis

In this work we present a comparative analysis of the performance of two recently proposed algorithms for signal subspace identification (SSI) and dimensionality reduction (DR) in hyperspectral data. Such SSI algorithms are robust to the presence of rare signal components and are particularly suitable when DR is adopted as a pre-processing step in small target detection applications.

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2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

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