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Proceedings Paper

Wavelet based hyperspectral image restoration using spatial and spectral penalties
Author(s): Behnood Rasti; Johannes R. Sveinsson; Magnus O. Ulfarsson; Jon Atli Benediktsson
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Paper Abstract

In this paper a penalized least squares cost function with a new spatial-spectral penalty is proposed for hyper- spectral image restoration. The new penalty is a combination of a Group LASSO (GLASSO) and First Order Roughness Penalty (FORP) in the wavelet domain. The restoration criterion is solved using the Alternative Direction Method of Multipliers (ADMM). The results are compared with other restoration methods where the proposed method outperforms them for the simulated noisy data set based on Signal to Noise Ratio (SNR) and visually outperforms them on a real degraded data set.

Paper Details

Date Published: 17 October 2013
PDF: 8 pages
Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 88920I (17 October 2013); doi: 10.1117/12.2029257
Show Author Affiliations
Behnood Rasti, Univ. of Iceland (Iceland)
Johannes R. Sveinsson, Univ. of Iceland (Iceland)
Magnus O. Ulfarsson, Univ. of Iceland (Iceland)
Jon Atli Benediktsson, Univ. of Iceland (Iceland)

Published in SPIE Proceedings Vol. 8892:
Image and Signal Processing for Remote Sensing XIX
Lorenzo Bruzzone, Editor(s)

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