Extended extinction profile for the classification of hyperspectral images

Pedram Ghamisi, R. Souza, J. Benediktsson, Xiaoxiang Zhu, L. Rittner, R. Lotufo
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引用次数: 1

Abstract

In this paper, a novel approach is proposed for the spectral-spatial classification of hyperspectral images. The proposed classification approach is based on a novel filtering technique, here entitled as extended extinction profile (EEP). The proposed classification approach is applied on two well-known data sets: Pavia University and Indian Pines; and the obtained results have been compared with one of the strongest filtering approaches in the literature named extended attribute profile (EAP). Results confirm that the proposed approach is able to efficiently extract spatial information for the classification of hyperspectral images.
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用于高光谱图像分类的扩展消光轮廓
本文提出了一种新的高光谱图像光谱空间分类方法。提出的分类方法是基于一种新的滤波技术,这里被称为扩展消光剖面(EEP)。本文提出的分类方法应用于两个著名的数据集:Pavia University和Indian Pines;并将所得结果与文献中最强的过滤方法之一扩展属性配置文件(EAP)进行了比较。实验结果表明,该方法能够有效地提取高光谱图像的空间信息。
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