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Journal of Electronic Imaging

Exploiting spatiospectral correlation for impulse denoising in hyperspectral images
Author(s): Hemant Kumar Aggarwal; Angshul Majumdar
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Paper 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 ℓ1-norm regularized ℓ1-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.

Paper Details

Date Published: 17 February 2015
PDF: 6 pages
J. Electron. Imag. 24(1) 013027 doi: 10.1117/1.JEI.24.1.013027
Published in: Journal of Electronic Imaging Volume 24, Issue 1
Show Author Affiliations
Hemant Kumar Aggarwal, Indraprastha Institute of Information Technology (India)
Angshul Majumdar, Indraprastha Institute of Information Technology (India)

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