高斯模糊

其他

发布时间 : 2021-01-02 15:19

阅读 :

import cv2 as cv
import numpy as np


def clamp(pv):
    if pv > 255:
        return 255
    if pv < 0:
        return 0
    else:
        return pv


def gaussian_noise(image):
    h, w, c = image.shape
    for row in range(h):
        for col in range(w):
            s = np.random.normal(0, 20, 3)
            b = image[row, col, 0]  # blue
            g = image[row, col, 1]  # green
            r = image[row, col, 2]  # red
            image[row, col, 0] = clamp(b + s[0])
            image[row, col, 1] = clamp(g + s[1])
            image[row, col, 2] = clamp(r + s[2])
    cv.imshow('noise image', image)


src = cv.imread('./0.png')  # blue, green, red
cv.namedWindow('input image', cv.WINDOW_AUTOSIZE)
cv.imshow('input image', src)
t1 = cv.getTickCount()
gaussian_noise(src)
t2 = cv.getTickCount()
time = (t2 - t1) / cv.getTickFrequency()
print('time count: {}'.format(time * 1000))
dst = cv.GaussianBlur(src, (5, 5), 0)
cv.imshow('Gaussian Blur', dst)
cv.waitKey(0)

cv.destroyAllWindows()

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