Python OpenCV图像复原的实现步骤

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

# 读取图像
image_path = 'path_to_your_image.jpg'  # 请替换为你的图像路径
image = cv2.imread(image_path)
if image is None:
    print(f"Error: Unable to load image at {image_path}")
    exit()

# 显示原始图像
plt.subplot(2, 2, 1)
plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
plt.title('Original Image')
plt.xticks([]), plt.yticks([])

# 均值滤波去噪
mean_filtered = cv2.blur(image, (5, 5))
plt.subplot(2, 2, 2)
plt.imshow(cv2.cvtColor(mean_filtered, cv2.COLOR_BGR2RGB))
plt.title('Mean Filtered Image')
plt.xticks([]), plt.yticks([])

# 高斯滤波去噪
gaussian_filtered = cv2.GaussianBlur(image, (5, 5), 1.0)
plt.subplot(2, 2, 3)
plt.imshow(cv2.cvtColor(gaussian_filtered, cv2.COLOR_BGR2RGB))
plt.title('Gaussian Filtered Image')
plt.xticks([]), plt.yticks([])

# 中值滤波去噪
median_filtered = cv2.medianBlur(image, 5)
plt.subplot(2, 2, 4)
plt.imshow(cv2.cvtColor(median_filtered, cv2.COLOR_BGR2RGB))
plt.title('Median Filtered Image')
plt.xticks([]), plt.yticks([])

# 显示所有图像
plt.show()

# 高斯模糊处理
blurred_image = cv2.GaussianBlur(image, (15, 15), 0)

# 显示模糊后的图像
plt.imshow(cv2.cvtColor(blurred_image, cv2.COLOR_BGR2RGB))
plt.title('Blurred Image')
plt.xticks([]), plt.yticks([])
plt.show()