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Proceedings Paper

Spectral correlation of natural ground terrain images at the spectral range of 0.4/1.05 um
Author(s): Eyal Agassi; Nissim Ben-Yosef; Amotz Wietz; Yehiel Vashdi
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Paper Abstract

Principal Component Analysis is a well-known statistical method which is commonly applied in the analysis of multispectral images. This paper presents some of the results that have been received by this method of multispectral images of natural background terrain at high spectral and spatial resolution in the spectral range of 0.4 - 1.05. The results show that images at the visible band and near IR are highly correlated within each band, but poorly correlated between bands. However, PC analysis shows that they are not independent spectral bands, since they have high correlation or anti-correlation with the main principal components. Another important finding is a `neutral wavelength,' which shows very little spectral difference between bare soil and vegetation. This wavelength can be used as an indicator for vegetation types and seasonal changes, and for spectral enhancement at remotely sensed images in real time.

Paper Details

Date Published: 13 August 1993
PDF: 10 pages
Proc. SPIE 1971, 8th Meeting on Optical Engineering in Israel: Optical Engineering and Remote Sensing, (13 August 1993); doi: 10.1117/12.150991
Show Author Affiliations
Eyal Agassi, Israel Military Industries (Israel)
Nissim Ben-Yosef, Hebrew Univ. of Jerusalem (Israel)
Amotz Wietz, Hebrew Univ. in Jerusalem (Israel)
Yehiel Vashdi, IMI (Israel)

Published in SPIE Proceedings Vol. 1971:
8th Meeting on Optical Engineering in Israel: Optical Engineering and Remote Sensing
Moshe Oron; Itzhak Shladov; Yitzhak Weissman, Editor(s)

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