在python中使用opencv去除图像中的高密度噪声

import cv2
import numpy as np

image = cv2.imread('image.jpg')

gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

blurred = cv2.GaussianBlur(gray, (5, 5), 0)

thresh = cv2.adaptiveThreshold(blurred, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 11, 4)

kernel = np.ones((3, 3), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)

contours, hierarchy = cv2.findContours(opening.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

min_area = 500
filtered_contours = [cnt for cnt in contours if cv2.contourArea(cnt) > min_area]

mask = np.zeros_like(image)
cv2.drawContours(mask, filtered_contours, -1, (255, 255, 255), thickness=cv2.FILLED)

result = cv2.bitwise_and(image, mask)

cv2.imshow('Denoised Image', result)
cv2.waitKey(0)
cv2.destroyAllWindows()