# Source code for pysptools.noise.dnoise

#
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# Copyright (c) 2013-2014, Christian Therien
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[docs]def whiten(M): """ Whitens a HSI cube. Use the noise covariance matrix to decorrelate and rescale the noise in the data (noise whitening). Results in transformed data in which the noise has unit variance and no band-to-band correlations. Parameters: M: numpy array 2d matrix of HSI data (N x p). Returns: numpy array Whitened HSI data (N x p). Reference: Krizhevsky, Alex, Learning Multiple Layers of Features from Tiny Images, MSc thesis, University of Toronto, 2009. See Appendix A. """ sigma = util.cov(M) U,S,V = np.linalg.svd(sigma) S_1_2 = S**(-0.5) S = np.diag(S_1_2.T) Aw = np.dot(V, np.dot(S, V.T)) return np.dot(M, Aw)