Paper
19 May 2016 An algorithm of remotely sensed hyperspectral image fusion based on spectral unmixing and feature reconstruction
Xuejian Sun, Lifu Zhang, Yi Cen, Mingyue Zhang
Author Affiliations +
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.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xuejian Sun, Lifu Zhang, Yi Cen, and 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); https://doi.org/10.1117/12.2225912
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Cited by 1 scholarly publication.
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KEYWORDS
Hyperspectral imaging

Image fusion

Multispectral imaging

Spatial resolution

Data fusion

Reconstruction algorithms

Image restoration

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