detect.py 文件源码

def ACE(M, t):
    """
    Performs the adaptive cosin/coherent estimator algorithm for target
    detection.

    Parameters:
        M: `numpy array`
            2d matrix of HSI data (N x p).

        t: `numpy array`
            A target endmember (p).

    Returns: `numpy array`
        Vector of detector output (N).

    References:
      X Jin, S Paswater, H Cline.  "A Comparative Study of Target Detection
      Algorithms for Hyperspectral Imagery."  SPIE Algorithms and Technologies
      for Multispectral, Hyperspectral, and Ultraspectral Imagery XV.  Vol
      7334.  2009.
    """
    N, p = M.shape
    # Remove mean from data
    u = M.mean(axis=0)
    M = M - np.kron(np.ones((N, 1)), u)
    t = t - u;

    R_hat = np.cov(M.T)
    G = lin.inv(R_hat)

    results = np.zeros(N, dtype=np.float32)
    ##% From Broadwater's paper
    ##%tmp = G*S*inv(S.'*G*S)*S.'*G;
    tmp = np.array(np.dot(t.T, np.dot(G, t)))
    dot_G_M = np.dot(G, M[0:,:].T)
    num = np.square(np.dot(t, dot_G_M))
    for k in range(N):
        denom = np.dot(tmp, np.dot(M[k], dot_G_M[:,k]))
        results[k] = num[k] / denom
    return results