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Beyond the resolution limit: using least squares for subpixel analysis in remote sensing

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1 Author(s)
Stan, S.S. ; Dept. of Comput. & Appl. Math., Univ. of the Witwatersrand, Johannesburg, South Africa

Spectral unmixing against a library of known endmembers can be modelled as a linear least squares problem with constraints. We take a different approach: model parameters are mapped through the log-odds transformation into a space where maximum likelihood parameter estimation leads to an unconstrained nonlinear least squares problem. Newton's method is then proposed for its resolution

Published in:

AFRICON, 1996., IEEE AFRICON 4th  (Volume:2 )

Date of Conference:

24-27 Sep 1996