http://scholars.ntou.edu.tw/handle/123456789/18294
標題: | A Novel Classification Processing Based on The Spatial Information and The Concept of Adaboost for Hyperspectral Image Classification | 作者: | Bor-Chen Kuo Shih-Syun Lin Huey-Min Wu Chun-Hsiang Chuang |
關鍵字: | Classification algorithms;Feature extraction;Hyperspectral imaging;Training;Nickel | 公開日期: | 25-七月-2010 | 出版社: | IEEE | 摘要: | 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. |
URI: | http://scholars.ntou.edu.tw/handle/123456789/18294 | ISSN: | 2153-7003 | DOI: | 10.1109/IGARSS.2010.5650388 |
顯示於: | 資訊工程學系 |
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