Morphological component analysis for feature detection in satellite images

IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003 Pub Date : 2003-10-27 DOI:10.1109/WARSD.2003.1295174

I. Koren, J. Joseph

引用次数: 1

Abstract

A new approach to cluster analysis is proposed, namely morphological component analysis (MCA), to enhance discrimination of features in multi-channel satellite images. The characterization of clusters, in this method, is morphological, unlike some of the classical cluster approaches in which the clusters are defined by their centers. By using the shape and orientation of the clusters, it is possible to define an affine transformation of the cluster space into a new one in which the selected clusters are orthogonal or better separated. Such an operation can be considered as supervised independent component analysis.

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用于卫星图像特征检测的形态成分分析

为了提高多通道卫星图像的特征识别能力，提出了一种新的聚类分析方法——形态成分分析(MCA)。在这种方法中，簇的表征是形态学的，不像一些经典的簇方法，其中簇是由它们的中心定义的。通过使用簇的形状和方向，可以将簇空间的仿射变换定义为一个新的簇空间，其中所选的簇是正交的或更好地分离。这样的操作可以看作是监督独立成分分析。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003

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