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Proceedings Paper

Shadow removal from VNIR hyperspectral remote sensing imagery with endmember signature analysis
Author(s): Fatih Omruuzun; Didem Ozisik Baskurt; Hazan Daglayan; Yasemin Yardimci Cetin
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Paper Abstract

This study aims to develop an effective regional shadow removal algorithm using rich spectral information existing in hyperspectral imagery. The proposed method benefits from spectral similarity of shadow and neighboring nonshadow pixels regardless of the intensity values. Although the shadow area has lower reflectance values due to inadequacy of incident light, it is expected that this area contains similar spectral characteristics with nonshadow area. Using this assumption, the endmembers in both shadowed and nonshadow area are extracted by Vertex Component Analysis (VCA). On the other hand, HySime algorithm overcomes estimating number of endmembers, which is one of the challenging parts in hyperspectral unmixing. Therefore, two sets of endmembers are extracted independently for both shadowed and nonshadow area. The proposed study aims at revealing the relation between these two endmember sets by comparing their pairwise similarities. Finally, reflectance values of shadowed pixels are re-calculated separately for each spectral band of hyperspectral image using this information.

Paper Details

Date Published: 3 June 2015
PDF: 8 pages
Proc. SPIE 9482, Next-Generation Spectroscopic Technologies VIII, 94821F (3 June 2015); doi: 10.1117/12.2190066
Show Author Affiliations
Fatih Omruuzun, Middle East Technical Univ. (Turkey)
Didem Ozisik Baskurt, Middle East Technical Univ. (Turkey)
Hazan Daglayan, Atilim Univ. (Turkey)
Yasemin Yardimci Cetin, Middle East Technical Univ. (Turkey)


Published in SPIE Proceedings Vol. 9482:
Next-Generation Spectroscopic Technologies VIII
Mark A. Druy; Richard A. Crocombe; David P. Bannon, Editor(s)

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