def ace_local_detector(hsi_img, tgt_sig, mask = None, guard_win = 2, bg_win = 4, beta = 0): """ Adaptive Cosine/Coherence Estimator with RX style local background estimation Inputs: hsi_image - n_row x n_col x n_band hyperspectral image tgt_sig - target signature (n_band x 1 - column vector) mask - binary image limiting detector operation to pixels where mask is true if not present or empty, no mask restrictions are used guard_win - guard window radius (square,symmetric about pixel of interest) bg_win - background window radius beta - scalar value used to diagonal load covariance Outputs: out - detector image 10/25/2012 - Taylor C. Glenn 6/2/2018 - Edited by Alina Zare 10/2018 - Python Implementation by Yutai Zhou """ n_row, n_col, n_band = hsi_img.shape mask = np.ones([n_row, n_col]) if mask is None else mask reg = beta * np.eye(n_band) out, kwargsout = rx_det(ace_local_helper, hsi_img, tgt_sig, mask = mask, guard_win = guard_win, bg_win = bg_win, reg = reg) return out, kwargsout
def smf_local_detector(hsi_img, tgt_sig, mask=None, guard_win=2, bg_win=4):
"""
Spectral Matched Filter with RX style local background estimation
Inputs:
hsi_image - n_row x n_col x n_band hyperspectral image
tgt_sig - target signature (n_band x 1 - column vector)
mask - binary image limiting detector operation to pixels where mask is true
if not present or empty, no mask restrictions are used
guard_win - guard window radius (square,symmetric about pixel of interest)
bg_win - background window radius
Outputs:
out - detector image
10/25/2012 - Taylor C. Glenn
10/2018 - Python Implementation by Yutai Zhou
"""
out, kwargsout = rx_det(smf_local_helper,
hsi_img,
tgt_sig,
mask=mask,
guard_win=guard_win,
bg_win=bg_win)
return out
def hsd_local_detector(hsi_img,
tgt_sig,
ems,
mask=None,
guard_win=2,
bg_win=4,
beta=0):
"""
Hybrid Subpixel Detector with RX style local background estimation
Inputs:
hsi_image - n_row x n_col x n_band hyperspectral image
tgt_sig - target signature (n_band x 1 - column vector)
mask - binary image limiting detector operation to pixels where mask is true
if not present or empty, no mask restrictions are used
guard_win - guard window radius (square,symmetric about pixel of interest)
bg_win - background window radius
beta - scalar value used to diagonal load covariance
Outputs:
out - detector image
1/25/2013 - Taylor C. Glenn
6/3/2018 - Edited by Alina Zare
12/2018 - Python Implementation by Yutai Zhou
"""
if tgt_sig.ndim == 1:
tgt_sig = tgt_sig[:, np.newaxis]
n_row, n_col, n_band = hsi_img.shape
hsi_data = hsi_img.reshape((n_row * n_col, n_band), order='F').T
reg = beta * np.eye(n_band)
# unmix data with only background endmembers
P = unmix(hsi_data, ems)
# unmix data with target signature as well
targ_P = unmix(hsi_data, np.hstack((tgt_sig, ems)))
out, kwargsout = rx_det(hsd_local_helper,
hsi_img,
tgt_sig,
mask,
guard_win,
bg_win,
ems=ems,
reg=reg,
P=P,
targ_P=targ_P)
return out