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Exploiting spatiospectral correlation for impulse denoising in hyperspectral images

[+] Author Affiliations
Hemant Kumar Aggarwal, Angshul Majumdar

Indraprastha Institute of Information Technology-Delhi, Okhla Industrial Estate, Phase III, Delhi 110020, India

J. Electron. Imaging. 24(1), 013027 (Feb 17, 2015). doi:10.1117/1.JEI.24.1.013027
History: Received August 15, 2014; Accepted January 13, 2015
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Abstract.  This paper proposes a technique for reducing impulse noise from corrupted hyperspectral images. We exploit the spatiospectral correlation present in hyperspectral images to sparsify the datacube. Since impulse noise is sparse, denoising is framed as an 1-norm regularized 1-norm data fidelity minimization problem. We derive an efficient split Bregman-based algorithm to solve the same. Experiments on real datasets show that our proposed technique, when compared with state-of-the-art denoising algorithms, yields better results.

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Hemant Kumar Aggarwal and Angshul Majumdar
"Exploiting spatiospectral correlation for impulse denoising in hyperspectral images", J. Electron. Imaging. 24(1), 013027 (Feb 17, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.1.013027


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