使用Python添加椒盐噪声

使用Python添加椒盐噪声可以通过OpenCV库来实现。首先，我们需要加载图像并将其转换为灰度图像。然后，我们可以使用OpenCV的`addSaltAndPepperNoise`函数向图像添加椒盐噪声。这个函数接受三个参数：图像、椒盐噪声比例和噪声密度。

下面是一个示例代码，演示如何使用Python添加椒盐噪声：

import cv2
import numpy as np

def add_salt_and_pepper_noise(image, salt_vs_pepper_ratio, noise_density):
    height, width = image.shape[:2]
    num_salt = int(height * width * noise_density * salt_vs_pepper_ratio)
    num_pepper = int(height * width * noise_density) - num_salt
    salt_coords = [np.random.randint(0, height, num_salt),
                   np.random.randint(0, width, num_salt)]
    pepper_coords = [np.random.randint(0, height, num_pepper),
                     np.random.randint(0, width, num_pepper)]
    image[salt_coords = 255
    image = 0
    return image

# 加载图像并转换为灰度图像
image = cv2.imread('image.jpg')
gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# 添加椒盐噪声
salt_vs_pepper_ratio = 0.5
noise_density = 0.01
noisy_image = add_salt_and_pepper_noise(gray_image, salt_vs_pepper_ratio, noise_density)

# 显示原始图像和添加椒盐噪声后的图像
cv2.imshow('Original Image', gray_image)
cv2.imshow('Noisy Image', noisy_image)
cv2.waitKey(0)
cv2.destroyAllWindows()

在这个示例中，我们首先加载图像并将其转换为灰度图像。然后，调用`add_salt_and_pepper_noise`函数来添加椒盐噪声。最后，我们使用OpenCV的`imshow`函数来显示原始图像和添加椒盐噪声后的图像。

请注意，`salt_vs_pepper_ratio`参数表示椒盐噪声中椒盐比例的权重，可以根据需要进行调整。`noise_density`参数表示噪声密度，控制噪声的强度。您可以根据实际情况调整这两个参数来达到所需的效果。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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