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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46495

Title: A novel classification processing based on the spatial information and the concept of Adaboost for hyperspectral image classification
Authors: Bor-Chen Kuo
Shih-Syun Lin
Huey-Min Wu
Chun-Hsiang Chuang
Contributors: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
Keywords: Adaboost;multiple classifier system;hyperspectral data
Date: 2010-07
Issue Date: 2018-05-21T06:26:52Z
Publisher: Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International
Abstract: Abstract:
In this paper, a novel classification processing based on the spatial information and the concept of Adaboost for hyperspectral image classification is proposed. This classification process is named as adaptive feature extraction with spatial information (AdaFESI). The main idea is adaptive in the sense that subsequent feature spaces are tweaked in favor of those instances misclassified by spectral or spatial classifiers in the previous feature space. All training samples are projected into these feature spaces to train various classifiers and then constitute a multiple classifier system. The experimental results based on two hyperspectral data sets show that the proposed algorithm can generate better classification results.
Relation: pp.2816-2819
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46495
Appears in Collections:[資訊工程學系] 演講及研討會

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