import numpy as np
import matplotlib.pyplot as plt
import cv2
import utilities
# TODO: The Image
img = cv2.imread(
'/Users/ariazare/Projects/Python/DEP_C4/Fig0441(a)(characters_test_pattern).tif'
)
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
img_padded = np.zeros((img.shape[0] * 2, img.shape[1] * 2), 'float32')
img_padded[:img.shape[0], :img.shape[1]] = img
img_padded = utilities.center_frequency(img_padded)
complex_img = [img_padded, np.zeros(img_padded.shape, 'float32')]
complex_img = cv2.merge(complex_img)
cv2.dft(complex_img, complex_img)
# MARK: The Filter
def creat_butterworth_filter(full_shape, radius, power):
butterworth_filter = np.zeros(full_shape, 'float32')
filter_p, filter_q = butterworth_filter.shape[0], butterworth_filter.shape[
1]
half_p = filter_p // 2
half_q = filter_q // 2
for i in range(filter_p):
import numpy as np
import matplotlib.pyplot as plt
import cv2
import utilities
# MARK: the image
img = cv2.imread(
'/Users/ariazare/Projects/Python/DEP_C4/Fig0462(a)(PET_image).tif')
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
img_padded = np.zeros((img.shape[0] * 2, img.shape[1] * 2), 'float32')
img_padded[:img.shape[0], :img.shape[1]] = img
img_padded = utilities.center_frequency(img_padded)
complex_img = [img_padded, np.zeros(img_padded.shape, 'float32')]
complex_img = cv2.merge(complex_img)
cv2.dft(complex_img, complex_img)
# MARK: the filter
def creat_homomorphic_filter(full_shape, yh, yl, c, radius):
homomorphic_filter = np.zeros(full_shape, 'float32')
filter_p, filter_q = homomorphic_filter.shape[0], homomorphic_filter.shape[
1]
half_p = filter_p // 2
half_q = filter_q // 2
for i in range(filter_p):
for j in range(filter_q):
import numpy as np
import cv2
import matplotlib.pyplot as plt
import utilities
from mpl_toolkits.mplot3d import axes3d
# MARK: image
img = cv2.imread(
'/Users/ariazare/Projects/Python/DEP_C4/Fig0438(a)(bld_600by600).tif')
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
img_padded = np.zeros((602, 602), 'float32')
img_padded[:-2, 0:-2] = img
img_centered = utilities.center_frequency(img_padded)
complex_img = [
np.array(img_centered, 'float32'),
np.zeros(img_centered.shape, 'float32')
]
complex_img = cv2.merge(complex_img)
cv2.dft(complex_img, complex_img)
# img_mag = utilities.get_magnitude(complex_img)
# img_mag = cv2.log(img_mag,img_mag)
# img_phase = utilities.get_phase_angel(complex_img)
# plt.imshow(img_mag, 'Greys')
# plt.show()
# MARK: sobel filter kernal
sobel_filter = np.array(
[[0, 0, 0, 0], [0, -1, 0, 1], [0, -2, 0, 2], [0, -1, 0, 1]], 'float32')