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Conference Paper: Cross-track illumination correction for hyperspectral pushbroom sensors using total variation and sparsity regularization

TitleCross-track illumination correction for hyperspectral pushbroom sensors using total variation and sparsity regularization
Authors
KeywordsHyperspectral destriping
Smile effect
Spectral smile correction
Hyperspectral denoising
Issue Date2020
Citation
2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 8-11 June 2020. In Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020 How to Cite?
AbstractCross-track illumination error exists in hyperspectral pushbroom sensor, who scan objects line-by-line with a detector array. When the illumination sensitivity of the individual detectors is not aligned well, or some detectors are degraded/aged, acquired images show non-uniform illumination in the cross-track direction. Meanwhile, because of the line-by-line scanning scheme, the cross-track illumination error is replicated along the flying track. Considering the structure of illumination error cross/along the track, we propose a column (along-track) mean compensation approach with total variation and sparsity regularization (COMCO-TVS), which corrects the illumination via exploiting characteristics of column-mean pixels and column-mean illumination errors: piecewise smoothness and sparsity, respectively, in the spatial-spectral domain. The correction effectiveness of the proposed method is illustrated using semi-real data.
Persistent Identifierhttp://hdl.handle.net/10722/297983

 

DC FieldValueLanguage
dc.contributor.authorZhuang, Lina-
dc.contributor.authorNg, Michael K.-
dc.date.accessioned2021-04-08T03:07:24Z-
dc.date.available2021-04-08T03:07:24Z-
dc.date.issued2020-
dc.identifier.citation2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 8-11 June 2020. In Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop, 2020-
dc.identifier.urihttp://hdl.handle.net/10722/297983-
dc.description.abstractCross-track illumination error exists in hyperspectral pushbroom sensor, who scan objects line-by-line with a detector array. When the illumination sensitivity of the individual detectors is not aligned well, or some detectors are degraded/aged, acquired images show non-uniform illumination in the cross-track direction. Meanwhile, because of the line-by-line scanning scheme, the cross-track illumination error is replicated along the flying track. Considering the structure of illumination error cross/along the track, we propose a column (along-track) mean compensation approach with total variation and sparsity regularization (COMCO-TVS), which corrects the illumination via exploiting characteristics of column-mean pixels and column-mean illumination errors: piecewise smoothness and sparsity, respectively, in the spatial-spectral domain. The correction effectiveness of the proposed method is illustrated using semi-real data.-
dc.languageeng-
dc.relation.ispartofProceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop-
dc.subjectHyperspectral destriping-
dc.subjectSmile effect-
dc.subjectSpectral smile correction-
dc.subjectHyperspectral denoising-
dc.titleCross-track illumination correction for hyperspectral pushbroom sensors using total variation and sparsity regularization-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/SAM48682.2020.9104285-
dc.identifier.scopuseid_2-s2.0-85092468218-
dc.identifier.eissn2151-870X-
dc.identifier.issnl1551-2282-

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