Wavelet based hyperspectral image restoration using spatial and spectral penalties

Behnood Rasti; Johannes R. Sveinsson; Magnus O. Ulfarsson; Jon Atli Benediktsson

doi:10.1117/12.2029257

17 October 2013 Wavelet based hyperspectral image restoration using spatial and spectral penalties

Behnood Rasti, Johannes R. Sveinsson, Magnus O. Ulfarsson, Jon Atli Benediktsson

Proceedings Volume 8892, Image and Signal Processing for Remote Sensing XIX; 88920I (2013) https://doi.org/10.1117/12.2029257
Event: SPIE Remote Sensing, 2013, Dresden, Germany

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.

Citation Download Citation

Behnood Rasti, Johannes R. Sveinsson, Magnus O. Ulfarsson, and Jon Atli Benediktsson "Wavelet based hyperspectral image restoration using spatial and spectral penalties", Proc. SPIE 8892, Image and Signal Processing for Remote Sensing XIX, 88920I (17 October 2013); https://doi.org/10.1117/12.2029257

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