Translation in Python of the Vertex Component Analysis method to extract aset of endmembers (elementary spectrum) from a given hyperspectral image.

More details on the method:

Jose M. P. Nascimento and Jose M. B. Dias

"Vertex Component Analysis: A Fast Algorithm to Unmix Hyperspectral Data" submited to IEEE Trans. Geosci. Remote Sensing, vol. .., no. .., pp. .-., 2004

Ae, indice, Yp = vca(Y,R,verbose = True,snr_input = 0)

Y - matrix with dimensions L(channels) x N(pixels) each pixel is a linear mixture of R endmembers signatures Y = M x s, where s = gamma x alfa gamma is a illumination perturbation factor and alfa are the abundance fractions of each endmember. NB: Y has to be a numpy array

R - positive integer number of endmembers in the scene

Ae - estimated mixing matrix (endmembers signatures)

indice - pixels that were chosen to be the most pure

Yp - Data matrix Y projected.

snr_input - (float) signal to noise ratio (dB)

verbose - [True | False]

Scipy needs to be installed.

Author: Adrien Lagrange ([email protected])

This code is a translation of a matlab code provided by Jose Nascimento ([email protected]) and Jose Bioucas Dias ([email protected]) available at http://www.lx.it.pt/~bioucas/code.htm under a non-specified Copyright (c)

Translation of last version at 22-February-2018 (Matlab version 2.1 (7-May-2004))

Under Apache 2.0 license