opencv_tutorials/python/code_025/opencv_025.py at master · HZHCoder1990/opencv_tutorials · GitHub

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import cv2 as cv

import numpy as np

def add_salt_pepper_noise(image):

h, w = image.shape[:2]

nums = 10000

rows = np.random.randint(0, h, nums, dtype=np.int)

cols = np.random.randint(0, w, nums, dtype=np.int)

for i in range(nums):

if i % 2 == 1:

image[rows[i], cols[i]] = (255, 255, 255)

else:

image[rows[i], cols[i]] = (0, 0, 0)

return image

def gaussian_noise(image):

noise = np.zeros(image.shape, image.dtype)

m = (15, 15, 15)

s = (30, 30, 30)

cv.randn(noise, m, s)

dst = cv.add(image, noise)

cv.imshow("gaussian noise", dst)

return dst

src = cv.imread("./test.png")

cv.imshow("input", src)

h, w = src.shape[:2]

src = gaussian_noise(src)

result1 = cv.blur(src, (5, 5))

cv.imshow("result-1", result1)

result2 = cv.GaussianBlur(src, (5, 5), 0)

cv.imshow("result-2", result2)

result3 = cv.medianBlur(src, 5)

cv.imshow("result-3", result3)

result4 = cv.fastNlMeansDenoisingColored(src, None, 15, 15, 10, 30)

cv.imshow("result-4", result4)

cv.waitKey(0)

cv.destroyAllWindows()

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