图像噪声、去噪基本方法合集（Python实现）

import numpy as np
import cv2
 
def add_gaussian_noise(image, mean=0, sigma=25):
    """
    添加高斯噪声
    """
    noise = np.random.normal(mean, sigma, image.shape)
    noisy_image = image + noise
    return np.clip(noisy_image, 0, 255).astype(np.uint8)
 
def median_filter(image, kernel_size=3):
    """
    中值滤波去噪
    """
    return cv2.medianBlur(image, kernel_size)
 
def custom_kernel_filter(image, kernel):
    """
    使用自定义核进行滤波去噪
    """
    return cv2.filter2D(image, -1, kernel)
 
def main():
    # 读取图像
    image = cv2.imread('input.jpg', 0)
    
    # 添加高斯噪声
    noisy_image = add_gaussian_noise(image)
    
    # 中值滤波去噪
    median_filtered_image = median_filter(noisy_image)
    
    # 自定义核滤波去噪
    custom_kernel = np.array([[-1, -1, -1], [-1, 9, -1], [-1, -1, -1]])
    custom_filtered_image = custom_kernel_filter(noisy_image, custom_kernel)
    
    # 显示和保存结果
    cv2.imshow('Original', image)
    cv2.imshow('Noisy Image', noisy_image)
    cv2.imshow('Median Filtered Image', median_filtered_image)
    cv2.imshow('Custom Kernel Filtered Image', custom_filtered_image)
    
    cv2.imwrite('noisy_image.jpg', noisy_image)
    cv2.imwrite('median_filtered_image.jpg', median_filtered_image)
    cv2.imwrite('custom_filtered_image.jpg', custom_filtered_image)
    
    cv2.waitKey(0)
    cv2.destroyAllWindows()
 
if __name__ == '__main__':
    main()

这段代码首先定义了添加高斯噪声和中值滤波去噪的函数，然后定义了一个主函数main来读取图像，应用噪声、进行去噪，并显示和保存结果。这个例子展示了如何使用Python和OpenCV库来处理图像噪声。