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Content Provider | IEEE Xplore Digital Library |
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Author | Zortea, M. Haertel, V. Clarke, R. |
Copyright Year | 2004 |
Abstract | High-dimensional image data open new possibilities in remote sensing digital image classification, particularly when dealing with classes that are spectrally very similar. The main problem refers to the estimation of a large number of classifier's parameters. One possible solution to this problem consists in reducing the dimensionality of the original data without a significant loss of information. In this letter, a new approach to reduce data dimensionality is proposed. In the proposed methodology, each pixel's curve of spectral response is initially segmented, and the digital numbers (DNs) at each segment are replaced by a smaller number of statistics. In this letter, the proposed statistics are the mean and variance of the segment's DNs, which are supposed to carry information about the segment's position and shape, respectively. Tests were performed by using Airborne Visible/Infrared Imaging Spectrometer hyperspectral image data. The experiments have shown that this methodology is capable of providing very acceptable results, in addition of being computationally efficient |
Sponsorship | IEEE Geoscience and Remote Sensing Society |
Starting Page | 107 |
Ending Page | 111 |
Page Count | 5 |
File Size | 344320 |
File Format | |
ISSN | 1545598X |
Volume Number | 4 |
Issue Number | 1 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2007-01-01 |
Publisher Place | U.S.A. |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Feature extraction Remote sensing Image segmentation Statistics Digital images Shape Testing Performance evaluation Infrared imaging Infrared spectra high-dimensional image data feature reduction |
Content Type | Text |
Resource Type | Article |
Subject | Electrical and Electronic Engineering Geotechnical Engineering and Engineering Geology |
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