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')