Loading [a11y]/accessibility-menu.js
Hyperspectral Band Selection via Rank Minimization | IEEE Journals & Magazine | IEEE Xplore

Hyperspectral Band Selection via Rank Minimization


Abstract:

Band selection is an important preprocessing technique for hyperspectral imagery, through which a subset of critical and representative spectral bands can be selected fro...Show More

Abstract:

Band selection is an important preprocessing technique for hyperspectral imagery, through which a subset of critical and representative spectral bands can be selected from a raw image cube for compact yet effect representation. Among the valid selection strategies, performing band selection in an unsupervised manner is usually considered more general due to its application-independent characteristic. This letter proposed a novel unsupervised hyperspectral band selector that can capture the interband redundancy nature of hyperspectral images through low-rank modeling. Experiments on three real-world hyperspectral data sets demonstrated that the proposed band selector can generate band subsets suitable in the context of hyperspectral pixel classification.
Published in: IEEE Geoscience and Remote Sensing Letters ( Volume: 14, Issue: 12, December 2017)
Page(s): 2320 - 2324
Date of Publication: 14 November 2017

ISSN Information:

Funding Agency:


References

References is not available for this document.