new_pixel = 0
for i in range(-1, 2):
for j in range(-1, 2):
if i == 0 or j == 0:
members1.append(img[x + i, y + j]) # 중간값을찾는다.
if (i != 0 and j != 0) or (i == 0 and j == 0):
members2.append(img[x + i, y + j]) # 중간값을찾는다.
members1.sort()
members2.sort()
members3 = [members1[2], members2[2], img[x, y]]
members3.sort()
new_pixel = members3[1]
# print(int(new_pixel),end=' ')
new_img.itemset(x, y, new_pixel)
# print()
return new_img
if __name__ == '__main__':
img = openimg.gray_imload('Lenna.png')
noise = salt_pepper.salt_pepper(img)
new_img = h_median(img)
cv2.imshow('img', img)
cv2.imshow('noise', noise)
cv2.imshow('new_img', new_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
import cv2
import numpy as np
import openimg
import immask
def gaussian_smooth_mask(mode=0):
mask = [[[1 / 16, 1 / 8, 1 / 16], [1 / 8, 1 / 4, 1 / 8],
[1 / 16, 1 / 8, 1 / 16]],
[[1 / 273, 4 / 273, 7 / 273, 4 / 273, 1 / 273],
[4 / 273, 16 / 273, 26 / 273, 16 / 273, 4 / 273],
[7 / 273, 26 / 273, 41 / 273, 26 / 273, 7 / 273],
[4 / 273, 16 / 273, 26 / 273, 16 / 273, 4 / 273],
[1 / 273, 4 / 273, 7 / 273, 4 / 273, 1 / 273]]]
return mask[mode]
if __name__ == '__main__':
img = openimg.gray_imload('howell.jpg')
new_img = immask.img_mask(img, gaussian_smooth_mask(1))
cv2.imshow('img', img)
cv2.imshow('new_img', new_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
G = np.zeros((row, col), dtype=np.complex)
print(row, col)
for l in range(row):
print(l)
for k in range(col):
v = 0
for n in range(row):
for m in range(col):
v += img[n, m] * \
np.exp(-2j * np.pi * (m * k / row + n * l / col))
G[l, k] = v / (row * col)
return G
img = openimg.gray_imload("Lenna.png")
f = np.fft.fft2(img)
fshift = np.fft.fftshift(f)
magnitude_spectrum1 = 20 * np.log(np.abs(f))
magnitude_spectrum2 = 20 * np.log(np.abs(fshift))
plt.subplot(131), plt.imshow(img, cmap='gray')
plt.title('Input Image'), plt.xticks([]), plt.yticks([])
plt.subplot(132), plt.imshow(magnitude_spectrum1, cmap='gray')
plt.title('fft'), plt.xticks([]), plt.yticks([])
plt.subplot(133), plt.imshow(magnitude_spectrum2, cmap='gray')
plt.title('fft_suffle'), plt.xticks([]), plt.yticks([])
plt.show()
import cv2
import numpy as np
import openimg
import toBinary
import 침식
import 팽창
img = toBinary.toBinary(openimg.gray_imload("Lenna.png"))
new_img = 팽창.pangchang(침식.chimsick(img))
cv2.imshow("binary", img)
cv2.imshow("mopology", new_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
