如何改变图像中的噪点颜色？

Question

我正在尝试生成如下噪声图像：

我已经知道如何生成带有随机噪声的图像，但不知道如何更改噪声颜色。

import numpy as np
import cv2
import matplotlib.pyplot as plt

img = cv2.imread('/home/pourya/face/os.jpg')[...,::-1]/255.0
noise =  np.random.normal(loc=-1, scale=1, size=img.shape)

# noise overlaid over image
noisy = np.clip((img + noise*1.7),0,1)
noisy2 = np.clip((img + noise*1.6),0,1)

# noise multiplied by image:
# whites can go to black but blacks cannot go to white
noisy2mul = np.clip((img*(1 + noise*1.5)),0,1)
noisy4mul = np.clip((img*(1 + noise*1.4)),0,1)

noisy2mul = np.clip((img*(1 + noise*1.8)),0,1)
noisy4mul = np.clip((img*(1 + noise*1.7)),0,1)

# noise multiplied by bottom and top half images,
# whites stay white blacks black, noise is added to center
img2 = img*2
n2 = np.clip(np.where(img2 <= 1, (img2*(1 + noise*0.2)), (1-img2+1)*(1 + noise*0.2)*-1 + 2)/2, 0,1)
n4 = np.clip(np.where(img2 <= 1, (img2*(1 + noise*0.4)), (1-img2+1)*(1 + noise*0.4)*-1 + 2)/2, 0,1)


# norm noise for viz only
noise2 = (noise - noise.min())/(noise.max()-noise.min())
plt.figure(figsize=(20,20))
plt.imshow(np.vstack((np.hstack((img, noise2)),
                  np.hstack((noisy, noisy2)),
                  np.hstack((noisy2mul, noisy4mul)),
                  np.hstack((n2, n4)))))
plt.show()
plt.hist(noise.ravel(), bins=100)
plt.show()

使用上面的代码，我得到了以下结果。

如何生成与第一张图像相似的单色噪点？ 谢谢

Answer 1

这是在 Python/OpenCV 中执行此操作的一种方法。使用 numpy 作为掩码创建灰度噪声图像。创建彩色图像。使用噪声作为掩码执行 bitwise_and 组合 omg 和蓝色。

输入：

import cv2
import numpy as np

# load image and get dimensions
img = cv2.imread("zelda1.jpg")
hh, ww = img.shape[:2]

# create noise image (multiplier increase noise in result)
noise = (800*np.random.random((hh,ww))).clip(0,255).astype(np.uint8)

# make blue image
blue = np.full_like(img, (255,0,0))

# combine img and blue using noise as mask
img_masked = cv2.bitwise_and(img, img, mask=255-noise)
blue_masked = cv2.bitwise_and(blue, blue, mask=noise)
result = cv2.add(img_masked, blue_masked)
    
# write result to disk
cv2.imwrite("noise.jpg", noise)
cv2.imwrite("blue.jpg", blue)
cv2.imwrite("zelda1_blue_noise.jpg", result)

# display it
cv2.imshow("noise", noise)
cv2.imshow("blue", blue)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyAllWindows()

噪声图像：

蓝色图像：

结果：