19 May 2016 An algorithm of remotely sensed hyperspectral image fusion based on spectral unmixing and feature reconstruction
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Abstract
In order to get high spatial resolution hyperspectral data, many studies have examined methods to combine spectral information contained in hyperspectral image with spatial information contained in multispectral/panchromatic image. This paper developed a new hyperspectral image fusion method base on the non-negative matrix factorization (NMF) theory. Data sets obtained by the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) was used to evaluate the performance of the method. Experimental results show that the proposed algorithm can provide a good way to solve the problem of high spatial resolution hyperspectral data shortage.
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Xuejian Sun, Xuejian Sun, Lifu Zhang, Lifu Zhang, Yi Cen, Yi Cen, Mingyue Zhang, Mingyue Zhang, } "An algorithm of remotely sensed hyperspectral image fusion based on spectral unmixing and feature reconstruction", Proc. SPIE 9874, Remotely Sensed Data Compression, Communications, and Processing XII, 98740P (19 May 2016); doi: 10.1117/12.2225912; https://doi.org/10.1117/12.2225912
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