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 ioimport numpy as npim=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]#uiroot = 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_sdef 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() |
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
