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Objective determination of image end-members in spectral mixture analysisSpectral mixture analysis was shown to be a powerful, multifaceted tool for analysis of multi- and hyper-spectral data. The essence of the first phase of the approach is to determine a set of image end-members that best account for the spectral variance in an image cube within a constrained, linear least squares mixing model. The selection of the image end-member is usually achieved using a priori knowledge and successive trial and error solutions to refine the total number and physical location of the end-members. However, in many situations a more objective method of determining these essential components is desired. The problem of image end-member determination was approached objectively by using the inherent variance of the data. Unlike purely statistical methods such as factor analysis, this approach derives solutions that conform to a physically realistic model.
Document ID
Document Type
Conference Paper
Tompkins, Stefanie (Brown Univ. Providence, RI, United States)
Mustard, John F. (Brown Univ. Providence, RI, United States)
Pieters, Carle M. (Brown Univ. Providence, RI, United States)
Forsyth, Donald W. (Brown Univ. Providence, RI, United States)
Date Acquired
September 6, 2013
Publication Date
January 1, 1993
Publication Information
Publication: Lunar and Planetary Inst., Twenty-Fourth Lunar and Planetary Science Conference. Part 3: N-Z
Subject Category
Distribution Limits
Work of the US Gov. Public Use Permitted.

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