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24 September 2001 Chromaticity difference-based classification algorithm for imaging spectrometer data
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Proceedings Volume 4554, Object Detection, Classification, and Tracking Technologies; (2001) https://doi.org/10.1117/12.441638
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Liangpei Zhang, Hui Lin, and Deren Li "Chromaticity difference-based classification algorithm for imaging spectrometer data", Proc. SPIE 4554, Object Detection, Classification, and Tracking Technologies, (24 September 2001); https://doi.org/10.1117/12.441638
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