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In this paper a new algorithm for striping noise reduction in hyperspectral images is proposed. Signal dependent striping noise is reduced by exploiting the high degree of spectral correlation of the useful signal in hyperspectral data. The algorithm does not require the human intervention nor introduces significant radiometric distortions on the useful signal. Results obtained on simulated and real...
In this paper, a new algorithm for striping noise reduction in hyperspectral images is proposed. The new algorithm exploits the orthogonal subspace approach to estimate the striping component and to remove it from the image, preserving the useful signal. The algorithm does not introduce artifacts in the data and also takes into account the dependence on the signal intensity of the striping component...
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