python 圖像中值濾波 zero padding

python 對圖像椒鹽噪聲進行中值濾波，考慮邊界0填充

import cv2
import numpy as np

# Read image
img = cv2.imread("F:\lena.jpg",0)
H, W= img.shape


imarray = np.array(img)
probility = 0.05

#添加椒鹽噪聲
for i in range(H):
    for j in range(W):
        if np.random.random(1) < probility:
            if np.random.random(1) < 0.5:
                imarray[i, j] = 0
            else:
                imarray[i, j] = 255

im_salt_pepper = imarray

cv2.imshow("salt&pepper noised",im_salt_pepper)


# 中值濾波模板
K_size = 3

# 進行0填充
pad = K_size // 2

out = np.zeros((H , W), dtype=np.float)
#print(out.shape)
out[pad:pad+H, pad:pad+W] = im_salt_pepper.copy().astype(np.float)

#4個邊緣進行填充
out[0,1:H]   = 0
out[H+1,1:H] = 0
out[1:H,0]   = 0
out[1:H,H+1] = 0

#4個角進行填充
out[0,0] = out[H+1,H+1] = out[0,H+1]=out[H+1,0] = 0
tmp = out.copy()

for y in range(pad, H+pad):
    for x in range(pad, W+pad):
            out[y, x] = np.median(tmp[y-pad:y+pad, x-pad:x+pad])

output = out[pad:pad+H, pad:pad+W].astype(np.uint8)

print("out shape is ",output.shape)

cv2.imshow("denoised", output)
cv2.imshow("original",img)
56 cv2.waitKey(0)
cv2.destroyAllWindows()

結果如下：

 

 

 

 

可以看到，中值濾波對於椒鹽噪聲去除效果還是比較好的。