无法通过remove_small_objects消除噪音

时间:2019-03-08 03:51:20

标签: python opencv image-processing scikit-image image-morphology

我有一个黑白图像。我尝试通过remove_small_objects消除噪音。

import cv2 as cv
import numpy as np
from skimage import morphology

img = np.array([[255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],
                [255, 255,   0, 255,   0,   0,   0,   0, 255, 255, 255],
                [255, 255, 255, 255,   0,   0,   0,   0, 255,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0, 255,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255, 255,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0]])

cleaned = morphology.remove_small_objects(img, min_size=10, connectivity=1)
print(cleaned)

while True:
    cv.imshow('Demo', cleaned.astype(np.uint8))
    if cv.waitKey(1) & 0xFF == 27:
        break

cv.destroyAllWindows()

但是,它没有按我预期的那样工作。中间的白色像素255仍然存在。

我做错了吗?谢谢

enter image description here

1 个答案:

答案 0 :(得分:2)

来自docs(重点是我):

  

skimage.morphology.remove_small_objects(ar, min_size=64, connectivity=1, in_place=False)

     
    

删除小于指定大小的对象。

         

期望ar是带有标签对象的数组,并删除小于min_size的对象。 如果ar是bool,则首先标记图像。这会导致bool和0-and-1数组的行为不同。

  
import numpy as np
from skimage import io, morphology
import matplotlib.pyplot as plt

img = np.array([[255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],
                [255, 255,   0, 255,   0,   0,   0,   0, 255, 255, 255],
                [255, 255, 255, 255,   0,   0,   0,   0, 255,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0, 255,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255, 255,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0],
                [255, 255,   0,   0,   0,   0,   0,   0,   0,   0,   0]])

arr = img > 0
cleaned = morphology.remove_small_objects(arr, min_size=2)
cleaned = morphology.remove_small_holes(cleaned, min_size=2)

fig, axs = plt.subplots(1, 2)
axs[0].imshow(img, cmap='gray')
axs[0].set_title('img')
axs[1].imshow(cleaned, cmap='gray')
axs[1].set_title('cleaned')
plt.show(fig)

plot