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Proceedings Paper

Automated display of hyperspectral images with unsupervised segmentation
Author(s): Sangwook Lee; Jonghwa Lee; Chulhee Lee
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Paper Abstract

In this paper, we investigate automated display methods for hyperspectral images with unsupervised segmentation. First, we apply an unsupervised segmentation method, which will produce a number of unlabeled classes. Then, we choose the classes whose sizes are larger than a threshold value. Then, we apply a feature extraction method to the chosen classes and find dominant discriminant features, which are used to display the hyperspectral images. We also exploit the use of the principal component analysis for the display of hyperspectral images. Experimental images show that the color images produced by the proposed methods show interesting characteristics compared to the conventional pseudo-color image.

Paper Details

Date Published: 31 August 2009
PDF: 7 pages
Proc. SPIE 7455, Satellite Data Compression, Communication, and Processing V, 74550Y (31 August 2009); doi: 10.1117/12.826962
Show Author Affiliations
Sangwook Lee, Yonsei Univ. (Korea, Republic of)
Jonghwa Lee, Yonsei Univ. (Korea, Republic of)
Chulhee Lee, Yonsei Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 7455:
Satellite Data Compression, Communication, and Processing V
Bormin Huang; Antonio J. Plaza; Raffaele Vitulli, Editor(s)

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