A fast iterative algorithm for implementation of pixel purity index

By Chein-I. Chang, Antonio J. Plaza. IEEE Geoscience and Remote Sensing Letters, 2006

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Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis (2006, methodology): “been shown in various applications to be very effective in capturing targets of interest such as unsupervised linear spectral mixture analysis, unsupervised target detection and classification [5] and endmember extraction [ 23 ].”
A New Growing Method for Simplex-Based Endmember Extraction Algorithm (2006, methodology): “In the SGA, a newly developed concept, called virtual dimensionality (VD) [10], [11], which has recently shown success in determination of the number of endmembers for endmember extraction [9], [12], [ 13 ], is proposed to estimate such p. Most recently, a linear mixture model-based least squares er”
Constrained band selection for hyperspectral imagery (2006, methodology): “With this interpretation, the VD has shown to be an effective measure in estimating the number of dimensions required to be retained for DR [7]‐[ 9 ].”