红包：
lena椒盐噪声图片：
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# -*- coding: utf-8 -*-
"""
created on sat oct 14 22:16:47 2017
@author: don
"""
from tkinter import *
from skimage import io
import numpy as np
im=io.imread('lena_sp.jpg', as_grey=true)
im_copy_med = io.imread('lena_sp.jpg', as_grey=true)
im_copy_mea = io.imread('lena_sp.jpg', as_grey=true)
#io.imshow(im)
for i in range(0,im.shape[0]):
for j in range(0,im.shape[1]):
im_copy_med[i][j]=im[i][j]
im_copy_mea[i][j]=im[i][j]
#ui
root = tk()
root.title("lena")
root.geometry('300x200')
medl = label(root, text="中值滤波：")
medl.pack()
med_text = stringvar()
med = entry(root, textvariable = med_text)
med_text.set("")
med.pack()
meal = label(root, text="均值滤波：")
meal.pack()
mea_text = stringvar()
mea = entry(root, textvariable = mea_text)
mea_text.set("")
mea.pack()
def m_filter(x, y, step):
sum_s=[]
for k in range(-int(step/2),int(step/2)+1):
for m in range(-int(step/2),int(step/2)+1):
sum_s.append(im[x+k][y+m])
sum_s.sort()
return sum_s[(int(step*step/2)+1)]
def mean_filter(x, y, step):
sum_s = 0
for k in range(-int(step/2),int(step/2)+1):
for m in range(-int(step/2),int(step/2)+1):
sum_s += im[x+k][y+m] / (step*step)
return sum_s
def on_click():
if(med_text):
medstep = int(med_text.get())
for i in range(int(medstep/2),im.shape[0]-int(medstep/2)):
for j in range(int(medstep/2),im.shape[1]-int(medstep/2)):
im_copy_med[i][j] = m_filter(i, j, medstep)
if(mea_text):
meastep = int(mea_text.get())
for i in range(int(meastep/2),im.shape[0]-int(meastep/2)):
for j in range(int(meastep/2),im.shape[1]-int(meastep/2)):
im_copy_mea[i][j] = mean_filter(i, j, meastep)
io.imshow(im_copy_med)
io.imsave(str(medstep) + 'med.jpg', im_copy_med)
io.imshow(im_copy_mea)
io.imsave(str(meastep) + 'mea.jpg', im_copy_mea)
button(root, text="filtergo", command = on_click).pack()
root.mainloop()
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运行结果截图：
以上这篇python 实现中值滤波、均值滤波的方法就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持服务器之家。
原文链接：https://blog.csdn.net/Dooonald/article/details/78260299