对图像加入高斯白噪声和椒盐噪声的

Python实现方法如下：

1. 加入高斯白噪声：

import cv2
import numpy as np

img = cv2.imread('image.jpg', 0)
mean = 0
var = 100
sigma = var ** 0.5
gaussian = np.random.normal(mean, sigma, (img.shape[0], img.shape[1]))  # 生成高斯噪声
gaussian = gaussian.reshape(img.shape[0], img.shape[1]).astype('uint8')
img_gaussian = cv2.add(img, gaussian)  # 图像加上高斯噪声

cv2.imshow('Original Image', img)
cv2.imshow('Gaussian Noise', img_gaussian)
cv2.waitKey(0)

2. 加入椒盐噪声：

import cv2
import numpy as np

img = cv2.imread('image.jpg', 0)
noise_num = int(0.05 * img.shape[0] * img.shape[1])  # 噪声点数占总像素点数的5%
for i in range(noise_num):
    x = np.random.randint(0, img.shape[0] - 1)
    y = np.random.randint(0, img.shape[1] - 1)
    if np.random.randint(0, 2) == 0:
        img[x, y] = 0  # 椒噪声
    else:
        img[x, y] = 255  # 盐噪声

cv2.imshow('Original Image', img)
cv2.waitKey(0)

注意：在实际应用中，处理图像时需要先将像素值归一化到[0, 1]范围内，处理完成后再乘以255还原到[0, 255]范围。