Sparsity promoting iterated constrained endmember detection in hyperspectral imagery

July 1, 2007 in Journal Papers

Abstract:

An extension of the iterated constrained endmember (ICE) algorithm that incorporates sparsity-promoting priors to find the correct number of endmembers is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine the number of endmembers that are required for a particular scene. The number of endmembers is found by adding a sparsity-promoting term to ICE’s objective function.

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Citation:

A. Zare and P. Gader, “Sparsity promoting iterated constrained endmember detection in hyperspectral imagery,” IEEE Geosci. Remote Sens. Lett., vol. 4, iss. 3, pp. 446-450, 2007. 
@Article{zare2007sparsitypromoting,
Title = {Sparsity promoting iterated constrained endmember detection in hyperspectral imagery},
Author = {Alina Zare and Paul Gader},
Journal = {IEEE Geosci. Remote Sens. Lett.},
Year = {2007},
Month = {July},
Number = {3},
Pages = {446 -450},
Volume = {4},
Doi = {10.1109/LGRS.2007.895727}}