Imaging Spectrometry: Spectral Resolution And Analytical Identification Of Spectral Features

Alexander F. H. Goetz; Wendy M. Calvin

doi:10.1117/12.942295

1 January 1987 Imaging Spectrometry: Spectral Resolution And Analytical Identification Of Spectral Features

Alexander F. H. Goetz, Wendy M. Calvin

Proceedings Volume 0834, Imaging Spectroscopy II; (1987) https://doi.org/10.1117/12.942295
Event: 31st Annual Technical Symposium on Optical and Optoelectronic Applied Sciences and Engineering, 1987, San Diego, CA, United States

Abstract

Spaceborne imaging spectrometers such as the High Resolution Imaging Spectrometer (HIRIS) are presently under development. Major trade-offs in weight, cost, and performance are related to the spatial, spectral, and radiometric resolution. In this paper, we have investigated the relationship between spectral and radiometric resolution by applying maximum likelihood classification and binary vector analysis to a set of model data. The model data consist of Gaussian spectral absorption features to which various levels of random noise have been applied. The results show that if the rapid, binary vector analysis techniques are to be used, feature depth-to-noise ratios of 10 or greater and Nyquist sampling are required to achieve acceptable classification errors. This translates into a NEAp of 0.5% for a 5% feature depth.

Citation Download Citation

Alexander F. H. Goetz and Wendy M. Calvin "Imaging Spectrometry: Spectral Resolution And Analytical Identification Of Spectral Features", Proc. SPIE 0834, Imaging Spectroscopy II, (1 January 1987); https://doi.org/10.1117/12.942295

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available