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# Material count classes

## HfcVd

class `material_count.``HfcVd`

  Computes the vitual dimensionality (VD) measure for an HSI image for specified false alarm rates.

  `count`(M, far='default', noise_whitening=False)

    Computes the vitual dimensionality (VD) measure for an HSI image for specified false alarm rates. When no false alarm rate(s) is specificied, the following vector is used: 1e-3, 1e-4, 1e-5. This metric is used to estimate the number of materials in an HSI scene.

    Parameters:
      M: numpy array
        HSI data as a 2D matrix (N x p).
      far: list [default default]
        False alarm rate(s).
      noise_whitening: boolean [default False]
        If True noise whitening is applied before calling HfcVd, doing a NWHFC.
    Returns: python list
      VD measure, number of materials estimate.
    References:

      C.-I. Chang and Q. Du, “Estimation of number of spectrally distinct signal sources in hyperspectral imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 3, mar 2004.

      J. Wang and C.-I. Chang, “Applications of independent component analysis in endmember extraction and abundance quantification for hyperspectral imagery,” IEEE Transactions on Geoscience and Remote Sensing, vol. 44, no. 9, pp. 2601-1616, sep 2006.

## HySime

class `material_count.``HySime`

  Hyperspectral signal subspace identification by minimum error.

  `count`(M)

    Hyperspectral signal subspace estimation.

    Parameters:
      M: numpy array
        Hyperspectral data set (each row is a pixel) with ((m*n) x p), where p is the number of bands and (m*n) the number of pixels.
    Returns: tuple integer, numpy array
      - kf signal subspace dimension
      - Ek matrix which columns are the eigenvectors that span the signal subspace.
    Reference:
      Bioucas-Dias, Jose M., Nascimento, Jose M. P., ‘Hyperspectral Subspace Identification’, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 46, NO. 8, AUGUST 2008.
    Copyright:
      Jose Nascimento (zen@isel.pt) & Jose Bioucas-Dias (bioucas@lx.it.pt) For any comments contact the authors.

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