python中的圓形中值濾波器

Question

我想創建一個給定半徑的圓形中值濾波器，而不是數組中的方形濾波器。 這裏是我的嘗試至今：

# Apply median filter to each image 
import matplotlib.pyplot as plt 
radius = 25 
disk_filter = plt.fspecial('disk', radius) 
w1_median_disk = plt.imfilter(w1data, disk_filter, 'replicate') 

w2_median_disk = plt.imfilter(w2data, disk_filter, 'replicate') 

w1data和w2data是我想要的過濾器適用於2-d numpy的陣列。 fspecial模塊來自Matlab，但我想在我的Python代碼中使用它（或其他類似的東西）。有任何想法嗎？

我得到錯誤信息「

disk_filter = plt.fspecial('disk', radius)
AttributeError: 'module' object has no attribute 'fspecial'"

我想知道，如果有任何一個模塊，我可以導入包含fspecial，或在Python等效的命令。

Answer 1

刮‘攝影師’從圖像：
https://www.mathworks.com/help/images/ref/fspecial.html

import numpy as np 
import matplotlib.pyplot as plt 

import os 
from scipy import misc 
path = 'D:/My Pictures/cameraman.bmp' 
cameraman = misc.imread(path, flatten=0) 

cameraman = np.average(cameraman, axis=2) 

r = 10 
y,x = np.ogrid[-r: r+1, -r: r+1] 
disk = x**2+y**2 <= r**2 
disk = disk.astype(float) 

from scipy import signal 
blur = signal.convolve2d(cameraman, disk, mode='full', boundary='fill', fillvalue=0) 

import matplotlib 
f, (ax1, ax2) = plt.subplots(1, 2, sharey=True) 
ax1.imshow(cameraman, cmap = matplotlib.cm.Greys_r) 
ax1.set_title('cameraman') 
ax2.imshow(blur, cmap = matplotlib.cm.Greys_r) 
ax2.set_title('signal.convolve2d(cameraman, disk..') 

，或者您可能需要使用scipy.ndimage.filters.convolve其「反映」邊緣處理

from scipy.ndimage.filters import convolve 
blur = convolve(cameraman, disk) 

Answer 2

如果你願意安裝/使用額外的包，我強烈推薦驚人skimage在Python中任何一種的圖像處理！與圓盤狀的過濾器過濾只是兩行代碼：

import skimage 
import skimage.data 
import skimage.morphology 
import skimage.filters 

# load example image 
original = skimage.data.camera() 

# create disk-like filter footprint with given radius 
radius = 10 
circle = skimage.morphology.disk(radius) 

# apply median filter with given footprint = structuring element = selem 
filtered = skimage.filters.median(original, selem = circle) 

Answer 3

這裏的東西我發現，似乎做的工作：

from scipy.ndimage.filters import generic_filter as gf 

# Define physical shape of filter mask 
def circular_filter(image_data, radius): 
    kernel = np.zeros((2*radius+1, 2*radius+1)) 
    y, x = np.ogrid[-radius:radius+1, -radius:radius+1] 
    mask = x**2 + y**2 <= radius**2 
    kernel[mask] = 1     
    filtered_image = gf(image_data, np.median, footprint = kernel) 
    return filtered_image 

但我不知道我完全理解這是怎麼回事上。特別是，究竟什麼行

 y, x = np.ogrid[-radius:radius+1, -radius:radius+1] 
    mask = x**2 + y**2 <= radius**2 
    kernel[mask] = 1 

呢？