Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 12, Issue 7, Pages 1411-1415Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2015.2404772
Keywords
Band selection (BS); column subset selection; hyperspectral image (HSI); unsupervised
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Funding
- National Natural Science Foundation of China [61422209]
- National Top Youth Talents Program of China
- Specialized Research Fund for the Doctoral Program of Higher Education [20130203110011]
- Fundamental Research Fund for the Central Universities [K5051202053]
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In this letter, we proposed a novel band selection algorithm for hyperspectral images (HSIs) based on column subset selection. The main idea of the proposed algorithm comes from the column subset selection problem in numerical linear algebra. It selects a group of bands, which maximizes the volume of the selected subset of columns. Since the high dimensionality decreases the contrast between bands, we use Manhattan distance to obtain a higher selection quality. Experimental results on real HSIs show that the proposed algorithm obtains competitively good results, in terms of classification accuracy, and is robust to noisy bands.
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