(编辑：jimmy 日期: 2024/9/28 浏览：2)
在matlab中，存在执行直接得函数来添加高斯噪声和椒盐噪声。Python-OpenCV中虽然不存在直接得函数，但是很容易使用相关的函数来实现。
代码：
import numpy as np
import random
import cv2
def sp_noise(image,prob):
'''
添加椒盐噪声
prob:噪声比例
'''
output = np.zeros(image.shape,np.uint8)
thres = 1 - prob
for i in range(image.shape[0]):
for j in range(image.shape[1]):
rdn = random.random()
if rdn < prob:
output[i][j] = 0
elif rdn > thres:
output[i][j] = 255
else:
output[i][j] = image[i][j]
return output
def gasuss_noise(image, mean=0, var=0.001):
'''
添加高斯噪声
mean : 均值
var : 方差
'''
image = np.array(image/255, dtype=float)
noise = np.random.normal(mean, var ** 0.5, image.shape)
out = image + noise
if out.min() < 0:
low_clip = -1.
else:
low_clip = 0.
out = np.clip(out, low_clip, 1.0)
out = np.uint8(out*255)
#cv.imshow("gasuss", out)
return out
可见，只要我们得到满足某个分布的多维数组，就能作为噪声添加到图片中。
例如：
import cv2 import numpy as np > im = np.empty((5,5), np.uint8) # needs preallocated input image > im array([[248, 168, 58, 2, 1], # uninitialized memory counts as random, too "htmlcode">img = ... noise = ... image = img + noise参考链接：
1、https://stackoverflow.com/questions/22937589/how-to-add-noise-gaussian-salt-and-pepper-etc-to-image-in-python-with-opencv#
2、https://stackoverflow.com/questions/14435632/impulse-gaussian-and-salt-and-pepper-noise-with-opencv#
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