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A STUDY ON THE IMAGE ANALYSIS METHODS OF IMAGING SPECTROMETER |
Shu Ning |
Wuhan Technical University of Surveying and Mapping |
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Abstract This paper introduces some analysis methods in recent years about imaging spectrometer data at home and abroad. Except the spectral match approach, the methods of the principal componant analysis, the optimal combination of the selected bands, the improved maximum likelihood method, the transformation based on the decision boundary feature matrix, and ortho-subspace projection approach are introduced. Some effects of these methods in application have been described as well.
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Keywords
Mutual information
Feature selection
Object-oriented classification
High spatial resolution image
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Issue Date: 02 August 2011
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[1] Joseph C Haranyi, et al. Hyperipectral Image Gaasification and Dimemsionality Reduction: An Orthogonal Subspace Projection Approach, IEEE Tns. Geosci. Remote Sensing, 1994, 32(4):[2] Jia Xiuping, et al. Efficient Maximum Likelihood Classification for Imaging Spectrometer Data Sets, IEEE Trans. Geosci.Remote Sensing, 1994, 32(2)[3] Jon Atli Benediktsson, et al, Classification and Feature Extraction of AVIRIS Data, IEEE Trans. Geosci. Remote Sensing,1995,33(5):[4] 舒宁.成像光谱仪影像的几种处理方法.武汉测绘科技大学学报,1997,22(4) |
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