使用Python-OpenCV向图片添加噪声的实现(高斯噪声、椒盐噪声)

2019-11-25 12:50:30

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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 npimport randomimport cv2def 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 outputdef 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 cv2import numpy as np>>> im = np.empty((5,5), np.uint8) # needs preallocated input image>>> imarray([[248, 168, 58,  2,  1], # uninitialized memory counts as random, too ? fun ;)     [ 0, 100,  2,  0, 101],    [ 0,  0, 106,  2,  0],    [131,  2,  0, 90,  3],    [ 0, 100,  1,  0, 83]], dtype=uint8)>>> im = np.zeros((5,5), np.uint8) # seriously now.>>> imarray([[0, 0, 0, 0, 0],    [0, 0, 0, 0, 0],    [0, 0, 0, 0, 0],    [0, 0, 0, 0, 0],    [0, 0, 0, 0, 0]], dtype=uint8)>>> cv2.randn(im,(0),(99))     # normalarray([[ 0, 76,  0, 129,  0],    [ 0,  0,  0, 188, 27],    [ 0, 152,  0,  0,  0],    [ 0,  0, 134, 79,  0],    [ 0, 181, 36, 128,  0]], dtype=uint8)>>> cv2.randu(im,(0),(99))     # uniformarray([[19, 53, 2, 86, 82],    [86, 73, 40, 64, 78],    [34, 20, 62, 80, 7],    [24, 92, 37, 60, 72],    [40, 12, 27, 33, 18]], dtype=uint8)

然后再：