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Proceedings Paper

Non-negative structural sparse representation for high resolution hyperspectral imaging
Author(s): Guiyu Meng; Guangyu Li; Weisheng Dong; Guangming Shi
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Paper Abstract

High resolution hyperspectral images have important applications in many areas, such as anomaly detection, target recognition and image classification. Due to the limitation of the sensors, it is challenging to obtain high spatial resolution hyperspectral images. Recently, the methods that reconstruct high spatial resolution hyperspectral images from the pair of low resolution hyperspectral images and high resolution RGB image of the same scene have shown promising results. In these methods, sparse non-negative matrix factorization (SNNMF) technique was proposed to exploit the spectral correlations among the RGB and spectral images. However, only the spectral correlations were exploited in these methods, ignoring the abundant spatial structural correlations of the hyperspectral images. In this paper, we propose a novel algorithm combining the structural sparse representation and non-negative matrix factorization technique to exploit the spectral-spatial structure correlations and nonlocal similarity of the hyperspectral images. Compared with SNNMF, our method makes use of both the spectral and spatial redundancies of hyperspectral images, leading to better reconstruction performance. The proposed optimization problem is efficiently solved by using the alternating direction method of multipliers (ADMM) technique. Experiments on a public database show that our approach performs better than other state-of-the-art methods on the visual effect and in the quantitative assessment.

Paper Details

Date Published: 4 November 2014
PDF: 11 pages
Proc. SPIE 9273, Optoelectronic Imaging and Multimedia Technology III, 92730H (4 November 2014); doi: 10.1117/12.2071661
Show Author Affiliations
Guiyu Meng, Xidian Univ. (China)
Guangyu Li, Xidian Univ. (China)
Weisheng Dong, Xidian Univ. (China)
Guangming Shi, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 9273:
Optoelectronic Imaging and Multimedia Technology III
Qionghai Dai; Tsutomu Shimura, Editor(s)

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