def get_padded_feature_stack(window_size, correction_switch, degree, pad=-1):
eigen_full=extract_polarimetric.eigen_raster_full(window_size, correction_switch, degree) #9 is the window size
cov_arr=extract_polarimetric.extract_covariance_arr(window_size, correction_switch, degree)
#padding=int(np.floor(window_size/2))
padding=window_size//2 if pad!=0 else 0
Ihh=np.pad(cov_arr[...,0,0], padding, 'constant')
Ihv=np.pad(cov_arr[...,1,1], padding, 'constant')
Ivv=np.pad(cov_arr[...,2,2], padding, 'constant')
arr_lamb1=np.pad(eigen_full[:,:,2], padding, 'constant')
arr_lamb2=np.pad(eigen_full[:,:,1], padding, 'constant')
arr_lamb3=np.pad(eigen_full[:,:,0], padding, 'constant')
co_pol_dif=np.pad(extract_polarimetric.co_pol_diff(cov_arr), padding, 'constant')
arr_det_cov=np.pad(np.absolute(extract_polarimetric.determinant_cov_conj(cov_arr)), padding, 'constant')
R_co = Rco_X = np.pad(np.real(cov_arr[...,0,2]), padding, 'constant')
Ico_X = np.pad(np.absolute(np.imag(cov_arr[...,0,2])), padding, 'constant')
#return np.dstack((np.real(Ihh),np.real(Ihv),np.real(Ivv),np.real(arr_lamb1), np.real(arr_lamb2), np.real(arr_lamb3), np.absolute(co_pol_dif),R_co, Ico_X, np.absolute(arr_det_cov)))
return np.dstack((np.real(Ihh),np.real(Ihv),np.real(Ivv),np.real(arr_lamb1), np.real(arr_lamb2), np.real(arr_lamb3), np.absolute(co_pol_dif), np.absolute(arr_det_cov)))#,R_co, Ico_X
def plot_feature_space_test(window_size):
eigen_arr = extract_polarimetric.eigen_raster_full(window_size)
cov_arr = extract_polarimetric.extract_covariance_arr(window_size, False)
cppr = np.absolute(extract_polarimetric.co_pol_power_ratio_1(cov_arr))
co_pol_diff = np.absolute(extract_polarimetric.co_pol_diff(cov_arr))
lambda_3 = np.absolute(eigen_arr[:, :, 0])
plot_feature_space(co_pol_diff, lambda_3)
def cloude_pottier(window_size):
fig, ax = plt.subplots(nrows=3, ncols=3)
arr = extract_polarimetric.eigen_raster_full(window_size)
cov_arr = extract_polarimetric.extract_covariance_arr(window_size)
plt.subplot(3, 3, 1)
plt.imshow(arr[:, :, 2], cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('lambda_1')
plt.colorbar()
plt.subplot(3, 3, 2)
plt.imshow(arr[:, :, 1], cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('lambda_2')
plt.colorbar()
plt.subplot(3, 3, 3)
plt.imshow(arr[:, :, 0], cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('lambda_3')
plt.colorbar()
plt.subplot(3, 3, 4)
plt.imshow(extract_polarimetric.entropy(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('Entropy')
plt.colorbar()
plt.subplot(3, 3, 5)
plt.imshow(extract_polarimetric.anisotropy(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('Anisotropy')
plt.colorbar()
plt.subplot(3, 3, 6)
plt.imshow(extract_polarimetric.pol_fraction(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('Pol_fraction')
plt.colorbar()
plt.subplot(3, 3, 7)
plt.imshow(extract_polarimetric.pedestal_height(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('pedestal_height')
plt.colorbar()
plt.show()
def read_Pol_features(window_size, correction_switch, degree, rescale_switch = False, log_Transform_switch = False):
#os.chdir('../')
eigen_full = extract_polarimetric.eigen_raster_full(window_size, correction_switch, degree) #9 is the window size
cov_arr = extract_polarimetric.extract_covariance_arr(window_size, correction_switch, degree)
arr_lamb1=np.absolute(eigen_full[:,:,2])
arr_lamb2=np.absolute(eigen_full[:,:,1])
arr_lamb3=np.absolute(eigen_full[:,:,0])
co_pol_dif=np.absolute(extract_polarimetric.co_pol_diff(cov_arr))
arr_det_cov=np.absolute(extract_polarimetric.determinant_cov_conj(cov_arr))
Rco_X = np.real(cov_arr[...,0,2])
Ico_X = abs(np.imag(cov_arr[...,0,2]))
I_hh = np.absolute(cov_arr[...,0,0])
I_hv = np.absolute(cov_arr[...,1,1])
I_vv = np.absolute(cov_arr[...,2,2])
if (log_Transform_switch ==True):
arr_lamb1 = np.log10(arr_lamb1)
arr_lamb2 = np.log10(arr_lamb2)
arr_lamb3 = np.log10(arr_lamb3)
co_pol_dif = np.log10(co_pol_dif)
arr_det_cov = np.log10(arr_det_cov)
Rco_X = np.log10(Rco_X)
Ico_X = np.log10(Ico_X)
I_hh = np.log10(I_hh)
I_hv = np.log10(I_hv)
I_vv = np.log10(I_vv)
if(rescale_switch == True):
arr_lamb1=rescale(arr_lamb1)
arr_lamb2=rescale(arr_lamb2)
arr_lamb3=rescale(arr_lamb3)
co_pol_dif = rescale(co_pol_dif)
arr_det_cov = rescale(arr_det_cov)
Rco_X = rescale(Rco_X)
Ico_X = rescale(Ico_X)
I_hh = rescale(I_hh)
I_hv = rescale(I_hv)
I_vv = rescale(I_vv)
#if(log_Transform_switch ==True):
#return 10*np.log10(np.dstack((arr_lamb1, arr_lamb2, arr_lamb3, co_pol_dif, arr_det_cov, Rco_X, Ico_X, I_hh, I_hv, I_vv)))
#else:
return np.dstack((arr_lamb1, arr_lamb2, arr_lamb3, co_pol_dif, arr_det_cov, Rco_X, Ico_X, I_hh, I_hv, I_vv))
def plot_all_UAVSAR_features(directory_MLC, window_size, correction_switch,
degree):
os.chdir(directory_MLC)
#ax = plt.subplots(3,3)
matplotlib.rcParams.update({'font.size': 3})
cov_arr = extract_polarimetric.extract_covariance_arr(
window_size, correction_switch, degree)
coh_arr = extract_polarimetric.extract_coherency_arr(
window_size, correction_switch, degree)
#===============1=============
plt.subplot(5, 4, 1)
plt.imshow(10 * np.log10(np.absolute(cov_arr[..., 0, 0])), cmap='gray')
plt.colorbar(label='dB')
plt.ylabel('Azimuth')
plt.title('$I_{HH}$')
plt.subplot(5, 4, 2)
plt.imshow(10 * np.log10(np.absolute(cov_arr[..., 1, 1])), cmap='gray')
plt.colorbar(label='dB')
#plt.ylabel('Azimuth')
plt.title('$I_{HV}$')
plt.subplot(5, 4, 3)
plt.imshow(10 * np.log10(np.absolute(cov_arr[..., 2, 2])), cmap='gray')
plt.colorbar(label='dB')
#plt.ylabel('Azimuth')
plt.title('$I_{VV}$')
#===============1=============
arr_co_pol_pow_ratio = extract_polarimetric.co_pol_power_ratio_1(cov_arr)
plt.subplot(5, 4, 4)
plt.imshow(np.absolute(arr_co_pol_pow_ratio), cmap='gray')
plt.colorbar()
#plt.ylabel('Azimuth')
plt.title('$\gamma_{CO}$')
#===============2=============
Rco_X = np.real(cov_arr[..., 0, 2])
Ico_X = np.imag(cov_arr[..., 0, 2])
plt.subplot(5, 4, 5)
plt.imshow(10 * np.log10(Rco_X), cmap='gray')
plt.colorbar(label='dB')
plt.title('$r_{CO}$')
plt.ylabel('Azimuth')
#===============6=============
plt.subplot(5, 4, 6)
plt.imshow(10 * np.log10(abs(Ico_X)), cmap='gray')
plt.colorbar(label='dB')
plt.title('$|i_{CO}|$')
#===============4=============
plt.subplot(5, 4, 7)
slc_dir = '/home/anurag/Documents/MScProject/SAR/OilSpill/North_Sea_UAVSAR/UAV_norway/UA_norway_00709_15092_000_150610_L090_CX_02'
sd_phase_diff = extract_polarimetric.sd_co_pol_phase_diff(slc_dir)
plt.imshow(np.absolute(sd_phase_diff), cmap='gray')
plt.colorbar()
plt.title('$\phi_{CO}$')
#===============5=============
plt.subplot(5, 4, 8)
plt.imshow(10 * np.log10(extract_polarimetric.determinant_cov(cov_arr)),
cmap='gray')
plt.colorbar(label='dB')
plt.title('$det (C_{FP})$')
#plt.ylabel('Azimuth')
#===============6=============
plt.subplot(5, 4, 9)
plt.imshow(10 *
np.log10(np.absolute(cov_arr[..., 0, 0] - cov_arr[..., 2, 2])),
cmap='gray')
plt.colorbar(label='dB')
plt.title('PD')
plt.ylabel('Azimuth')
#===============7=============
plt.subplot(5, 4, 10)
plt.imshow(np.absolute(cov_arr[..., 1, 1]) / np.absolute(
(cov_arr[..., 0, 0] + cov_arr[..., 2, 2])),
cmap='gray')
plt.colorbar()
plt.title('$P_{X}$')
#===============8=============
eigen_full = extract_polarimetric.eigen_raster_full(
window_size, correction_switch, degree)
arr_lamb1 = eigen_full[:, :, 2]
arr_lamb2 = eigen_full[:, :, 1]
arr_lamb3 = eigen_full[:, :, 0]
#===============8=============
plt.subplot(5, 4, 11)
plt.imshow(10 * np.log10(np.absolute(arr_lamb1)), cmap='gray')
plt.colorbar(label='dB')
plt.title('$\lambda_{1}$')
#===============9=============
plt.subplot(5, 4, 12)
plt.imshow(10 * np.log10(np.absolute(arr_lamb2)), cmap='gray')
plt.colorbar(label='dB')
#plt.ylabel('Azimuth')
plt.title('$\lambda_{2}$')
#===============10=============
plt.subplot(5, 4, 13)
plt.imshow(10 * np.log10(np.absolute(arr_lamb3)), cmap='gray')
plt.colorbar(label='dB')
plt.title('$\lambda_{3}$')
plt.ylabel('Azimuth')
#===============11=============
plt.subplot(5, 4, 14)
arr_ent = extract_polarimetric.entropy(eigen_full)
plt.imshow(10 * np.log10(np.absolute(arr_ent)), cmap='gray')
plt.colorbar()
plt.title('$H$')
#===============12=============
plt.subplot(5, 4, 15)
arr_pol_frac = extract_polarimetric.pol_fraction(eigen_full)
plt.imshow(arr_pol_frac, cmap='gray')
plt.colorbar()
plt.title('$PF$')
#===============13=============
plt.subplot(5, 4, 16)
arr_anisotropy = extract_polarimetric.anisotropy(eigen_full)
plt.imshow(arr_anisotropy, cmap='gray')
plt.colorbar()
#plt.xlabel('Range')
#plt.ylabel('Azimuth')
plt.title('$A$')
#================14==============
plt.subplot(5, 4, 17)
co_pol_corr_arr = extract_polarimetric.co_pol_correlation(cov_arr)
plt.imshow(np.absolute(co_pol_corr_arr), cmap='gray')
plt.colorbar()
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('$Co-pol Correlation$')
#================15==============
plt.subplot(5, 4, 18)
arr_conform_coeff = extract_polarimetric.conformity_coeff(cov_arr)
plt.imshow(np.absolute(arr_conform_coeff), cmap='gray')
plt.colorbar()
plt.xlabel('Range')
plt.title('Conformity Coefficient')
#================16==============
plt.subplot(5, 4, 19)
alpha = extract_polarimetric.mean_alpha_angle(eigen_full, window_size,
correction_switch, degree)
plt.imshow(alpha, cmap='gray')
plt.colorbar(label='degrees')
plt.title('Mean alpha angle')
plt.xlabel('Range')
#================16==============
plt.subplot(5, 4, 20)
PH = extract_polarimetric.pedestal_height(eigen_full)
plt.imshow(PH, cmap='gray')
plt.colorbar()
plt.title('PH')
plt.xlabel('Range')
plt.tight_layout()
plt.savefig(
'/home/anurag/Documents/MScProject/Meetings_ITC/Results/Features/Polarimetric_Features/Inc_corr_applied/Det_cov_conj.tiff',
dpi=300,
box_inches='tight',
papertype='a4',
orientation='portrait')
plt.show()
def cloude_pottier(window_size):
#fig, ax = plt.subplots(nrows=3, ncols=3)
arr = extract_polarimetric.eigen_raster_full(window_size)
cov_arr = extract_polarimetric.extract_covariance_arr(window_size, False)
#plt.subplot(3,3,1)
plt.imshow(arr[:, :, 2], cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('lambda_1')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'lambda_1' + '.tiff',
dpi=300)
plt.clf()
#plt.subplot(3,3,2)
plt.imshow(arr[:, :, 1], cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('lambda_2')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'lambda_2' + '.tiff',
dpi=300)
plt.clf()
#plt.subplot(3,3,3)
plt.imshow(arr[:, :, 0], cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('lambda_3')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'lambda_3' + '.tiff',
dpi=300)
plt.clf()
#plt.subplot(3,3,4)
plt.imshow(extract_polarimetric.entropy(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('Entropy')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'Entropy' + '.tiff',
dpi=300)
plt.clf()
#plt.subplot(3,3,5)
plt.imshow(extract_polarimetric.anisotropy(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('Anisotropy')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'Anisotropy' + '.tiff',
dpi=300)
plt.clf()
#plt.subplot(3,3,6)
plt.imshow(extract_polarimetric.pol_fraction(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('Pol_fraction')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'Pol_fraction' + '.tiff',
dpi=300)
plt.clf()
#plt.subplot(3,3,7)
plt.imshow(extract_polarimetric.pedestal_height(arr), cmap='gray')
plt.xlabel('Range')
plt.ylabel('Azimuth')
plt.title('pedestal_height')
plt.colorbar()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results/' +
'pedestal_height' + '.tiff',
dpi=300)
plt.clf()
plt.xlabel('Range')
plt.ylabel('dB')
plt.title('PO_TSx')
plt.tight_layout()
plt.savefig('/home/anurag/Documents/MScProject/Meetings_ITC/Results//Multifrequency/Detectability.tiff', dpi=300, papertype='a4', bbox_inches='tight')
plt.show()
'''
#=======multi_freq_ratio===========
#IVV_UAV=10*np.log10(np.absolute(C3_UAV_TS[...,2,2]))
#I_VV=np.absolute(TS_x[...,1])**2
#I_VV_TSX=10*np.log10(I_VV)
#multi_freq_ratio(IVV_UAV, I_VV_TSX)
#===========H-alpha decomposition==============
os.chdir(UAVSAR_directory_TSX)
eigen_raster_full = extract_polarimetric.eigen_raster_full(
window_size=9, correction_switch=False, degree=0)[35:815, 87:724, ...]
H = extract_polarimetric.entropy(eigen_raster_full)
A = extract_polarimetric.anisotropy(eigen_raster_full)
plt.imshow(A, cmap='jet')
plt.colorbar()
plt.show()