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Proceedings Paper

Chromaticity difference-based classification algorithm for imaging spectrometer data
Author(s): Liangpei Zhang; Hui Lin; Deren Li
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Paper Abstract

Hyperspectral remote sensing image classification generally adopts a direct spectral matching method. It is, however, inconvenient in the classification calculation because the complete reference spectra are needed. In this work we have developed a new chromaticity difference-based classification algorithm, which can be used to classify imaging spectrometer image data. In calculation, the algorithm itself is not directly relating to the number of spectral wavebands. It only needs three chromaticity coordinate parameters for both the image spectrum and the reference spectrum to complete the final classification calculation. In addition, the classification threshold for the algorithm can be easily set according to the color science theory, therefore, the classification results from the algorithm is reliable. Through a comparison with SAM algorithm, the performance of the new chromaticity difference-based classification algorithm was proved to be as good as SAM algorithm, but our algorithm was relatively simpler and flexible.

Paper Details

Date Published: 24 September 2001
PDF: 6 pages
Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); doi: 10.1117/12.441638
Show Author Affiliations
Liangpei Zhang, Wuhan Univ. (China)
Hui Lin, Chinese Univ. of Hong Kong (Hong Kong)
Deren Li, Wuhan Univ. (China)

Published in SPIE Proceedings Vol. 4554:
Object Detection, Classification, and Tracking Technologies
Jun Shen; Sharatchandra Pankanti; Runsheng Wang, Editor(s)

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