Integration of Spatial-Spectral Information for Resolution Enhancement in Hyperspectral Images

In this paper, a new algorithm is proposed for resolution enhancement in hyperspectral images (HSIs). The key techniques are included: spectral unmixing and superresolution mapping, by which spatial and spectral information of HSIs is substantially fused. The proposed algorithm first represents each...

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Bibliographic Details
Published in:IEEE transactions on geoscience and remote sensing 2008-05, Vol.46 (5), p.1347-1358
Main Authors: Yanfeng Gu, Yanfeng Gu, Ye Zhang, Ye Zhang, Junping Zhang, Junping Zhang
Format: Article
Language:English
Subjects:
Algorithms
Hyperspectral images (HSIs)
Hyperspectral imaging
Hyperspectral sensors
Image resolution
neural network
Neural networks
Object detection
Optical sensors
Remote sensing
resolution enhancement
Sensor arrays
Space technology
Spatial resolution
spectral unmixing
Studies
superresolution mapping
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Summary:In this paper, a new algorithm is proposed for resolution enhancement in hyperspectral images (HSIs). The key techniques are included: spectral unmixing and superresolution mapping, by which spatial and spectral information of HSIs is substantially fused. The proposed algorithm first represents each pixel in scene as a linear combination of landcover spectra and noise. Then, a fully constrained least squares algorithm is used to obtain the proportion of each landcover in each pixel, i.e., abundance, subjecting to two constraints: nonnegativity and sum-to-one. After that, superresolution mapping is performed on high-resolution grids according to spectral unmixing abundances of each landcover and following spatial correlation of clutters. Thus, by reasonably integrating spatial and spectral information of landcovers in HSIs, the proposed algorithm realizes resolution enhancement of the HSIs based on a back-propagation neural network. The proposed algorithm is independent from the a priori information associated with original HSIs, i.e., a main merit of the algorithm. In order to evaluate the performance of the new algorithm, numerical experiments are conducted on both simulated images and real HSIs collected by the Airborne Visible/Infrared Imaging Spectrometer. The proposed algorithm is compared with the traditional method in the experiments. The experimental results prove that the proposed algorithm effectively enhances the resolution of HSIs and indicate its applicability.
ISSN:0196-2892
1558-0644
DOI:10.1109/TGRS.2008.917270