OpenCV—模糊处理与高斯模糊
均值模糊与中值模糊
import cv2 as cv
import numpy as np
def blur_demo(img):
dst1 = cv.blur(img, (5, 5)) # 均值模糊
cv.imshow("blur_demo", dst1)
def median_blur_demo(img):
dst2 = cv.medianBlur(img, 9) # 中值模糊 有去椒盐的功能（去燥）
cv.imshow("medianBlur_demo", dst2)中值滤波处理椒盐噪声效果显著
自定义模糊
注意要做防止溢出处理
def custom_demo(img):
kernel = np.ones([5, 5], np.float32)/25
dst3 = cv.filter2D(img, -1, kernel=kernel) # 自定义模糊
cv.imshow("custom_demo", dst3)自定义锐化操作：
def custom_demo(img):
# kernel = np.ones([5, 5], np.float32)/25
kernel = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], np.float32)/9
dst3 = cv.filter2D(img, -1, kernel=kernel) # 自定义模糊
cv.imshow("custom_demo", dst3)高斯模糊
# 将范围定义在0-255之间
def clamp(pv):
if pv > 255:
return 255
elif pv < 0:
return 0
else:return pv
# 定义高斯噪声函数
def gaussian_demo(img): #高斯模糊
h, w, c = img.shape
for row in range(0, h, 1):
for col in range(0, w, 1):
s = np.random.normal(0, 20, 3)
b = img[row, col, 0] # blue
g = img[row, col, 1] # green
r = img[row, col, 2] # red
img[row, col, 0] = clamp(b + s[0])
img[row, col, 1] = clamp(g + s[1])
img[row, col, 2] = clamp(r + s[2])
cv.imshow("gaussian_demo", img)测试程序
import cv2 as cv
import numpy as np
def blur_demo(img):
dst1 = cv.blur(img, (5, 5)) # 均值模糊
cv.imshow("blur_demo", dst1)
def median_blur_demo(img):
dst2 = cv.medianBlur(img, 9) # 中值模糊 有去椒盐的功能（去燥）
cv.imshow("medianBlur_demo", dst2)
def custom_demo(img):
# kernel = np.ones([5, 5], np.float32)/25
kernel = np.array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], np.float32)/9
dst3 = cv.filter2D(img, -1, kernel=kernel) # 自定义模糊
cv.imshow("custom_demo", dst3)
# 将范围定义在0-255之间
def clamp(pv):
if pv > 255:
return 255
elif pv < 0:
return 0
else:return pv
# 定义高斯噪声函数
def gaussian_demo(img): #高斯模糊
h, w, c = img.shape
for row in range(0, h, 1):
for col in range(0, w, 1):
s = np.random.normal(0, 20, 3)
b = img[row, col, 0] # blue
g = img[row, col, 1] # green
r = img[row, col, 2] # red
img[row, col, 0] = clamp(b + s[0])
img[row, col, 1] = clamp(g + s[1])
img[row, col, 2] = clamp(r + s[2])
cv.imshow("gaussian_demo", img)
src1 = cv.imread("D:/JetBrains/PyCharm 2019.1.3/PycharmProjects/Study/opencv_study/Penguins.jpg") # 读取图像
src2 = cv.imread("D:/JetBrains/PyCharm 2019.1.3/PycharmProjects/Study/opencv_study/s.jpg")
cv.namedWindow("input img", cv.WINDOW_AUTOSIZE)
cv.imshow("input img", src1)
blur_demo(src1)
cv.imshow("input img2", src2)
median_blur_demo(src2)
custom_demo(src1)
gaussian_demo(src1)
dst = cv.GaussianBlur(src1, (0, 0), 5) # 高斯模糊的另外一种方法
cv.imshow("GaussianBlur", dst)
cv.waitKey(0)
cv.destroyAllWindows()
结果图：