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Hyperspectral Stripes Removal With Wavelet-Domain Low-Rank/Group-Sparse Decomposition

Pushbroom acquisition of hyperspectral imagery is prone to striping artifacts in the along-track direction. A hyperspectral destriping algorithm is proposed such that subbands of a 2D wavelet transform most effected by pushbroom stripes— namely, those with spatially vertical orientation—are the exclusive focus of destriping. The proposed method features an iterative image decomposition composed of a low-rank model for the stripes coupled with a group-sparse prior on the wavelet coefficients of the subbands in question. Experimental results on both synthetically striped imagery demonstrate superior image quality for the proposed method as compared to other state-of-the-art methods.