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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40574

Title: Fisher criterion based nearest feature line approach to land cover classification using multi source data fusion
Authors: Chang, Yang-Lang
Huang, Bormin
Han, Chin-Chuan
Chang, Lena
Hsieh, Tung-Ju
Fu, Yi-Shiang
Contributors: 國立臺灣海洋大學:通訊與導航工程學系
Keywords: band generation process
nearest feature line
multisource data fusion
Fisher criterion
Date: 2013
Issue Date: 2017-01-20T07:12:04Z
Publisher: SPIE, Satellite Data Compression, Satellite Data Compression, Communications, and Processing IX,
Abstract: Abstract: In this paper a novel technique, known as nearest feature line (NFL) approach, is proposed for supervised classification of multisource images for the purpose of landslide hazard assessment. This approach presents a framework for data fusion of multisource remotely sensed images, which consists of two approaches, referred to as band generation process (BGP) and Fisher criterion based NFL classifier. It is developed for land cover classification based on the fusion of remotely sensed images of the same scene collected from multiple sources. Compared to the original NFL, we propose an improve NFL classifier which uses the Fisher criterion of between-class and within-class discrimination to enhance the original one. In the training phase the labeled samples are discriminated by the Fisher criterion, which can be treated as a pre-processing of NFL. The classification results can be obtained by NFL algorithm. In order for the proposed NFL to be effective for multispectral images, a multiple adaptation BGP is introduced to create a new set of additional bands especially accommodated to landslide classes. Experimental results demonstrate the proposed BGP/NFL approach is suitable for land cover classification in earth remote sensing and improves the precision of image classification..
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40574
Appears in Collections:[通訊與導航工程學系] 演講及研討會

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