@inproceedings{3fb2afeb2c0c456a9a9e787662272153,
title = "Hyperspectral Stripes Removal with Wavelet-Domain Low-Rank/Group-Sparse Decomposition",
abstract = "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.",
keywords = "Destriping, group sparsity, hyperspectral imagery, low-rank decomposition, wavelet transform",
author = "Na Liu and Wei Li and Ran Tao and Fowler, {James E.} and Lina Yang",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2019 ; Conference date: 24-09-2019 Through 26-09-2019",
year = "2019",
month = sep,
doi = "10.1109/WHISPERS.2019.8921401",
language = "English",
series = "Workshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing",
publisher = "IEEE Computer Society",
booktitle = "2019 10th Workshop on Hyperspectral Imaging and Signal Processing",
address = "United States",
}