python中值滤波

中值滤波1

import numpy as np
import cv2
from PIL import Image
import scipy.signal as signal
import matplotlib.pyplot as plt

# 创建一个500*500的矩阵
input_images = np.zeros((500, 500))
filename = "E:/pycharm/GraduationDesign/Test/testtwo.png"
# convert将当前图像转换为灰度模式，并且返回新的图像。
# 将图片在重新定义的矩阵中再显示，不然可能会只显示部分。
img = Image.open(filename).resize((500, 500)).convert('L')
plt.subplot(221)
plt.title('原图', fontproperties=font_set)
plt.imshow(img)
# 图像的尺寸，按照像素数计算。它的返回值为宽度和高度的二元组（width, height）。
width = img.size[0]
height = img.size[1]
threshold = 130
# 可以改写代码使其成为二值化,此代码可理解为反向二值化
for h in range(height):
    for w in range(width):
        # getpixel直接获得（h，w）处的像素直接返回这个点三个通道的像素值
        # 返回给定位置的像素值。如果图像为多通道，则返回一个元组(r,g,b,阈值）。
        # 如果改成（w，h）出现的图像会倒转
        if img.getpixel((w, h)) < threshold:

            input_images[h, w] = 1
        else:
            input_images[h, w] = 0
plt.subplot(222)
plt.title('二值化', fontproperties=font_set)
plt.imshow(input_images)

data = signal.medfilt2d(np.array(img), kernel_size=3)  # 二维中值滤波
for h in range(0, height):
    for w in range(0, width):
        if data[h][w] < 128:
            input_images[h, w] = 0
        else:
            input_images[h, w] = 1

plt.subplot(223)
plt.title('中值滤波去噪（3*3）', fontproperties=font_set)
plt.imshow(input_images)

data = signal.medfilt2d(np.array(img), kernel_size=7)  # 二维中值滤波
for h in range(0, height):
    for w in range(0, width):
        if data[h][w] < 128:
            input_images[h, w] = 0
        else:
            input_images[h, w] = 1
plt.subplot(224)
plt.title('中值滤波去噪（7*7）', fontproperties=font_set)
plt.imshow(input_images)
plt.show()

中值滤波2

from PIL import Image
import numpy as np


def MedianFilter(src, dst, k=3, padding=None):
    imarray = np.array(Image.open(src))
    height, width = imarray.shape

    if not padding:
        edge = int((k - 1) / 2)
        if height - 1 - edge <= edge or width - 1 - edge <= edge:
            print("The parameter k is to large.")
            return None
        new_arr = np.zeros((height, width), dtype="uint8")
        for i in range(height):
            for j in range(width):
                if i <= edge - 1 or i >= height - 1 - edge or j <= edge - 1 or j >= height - edge - 1:
                    new_arr[i, j] = imarray[i, j]
                else:
                    # nm:neighbour matrix
                    nm = imarray[i - edge:i + edge + 1, j - edge:j + edge + 1]
                    max = np.max(nm)
                    min = np.min(nm)
                    if imarray[i, j] == max or imarray[i, j] == min:
                        new_arr[i, j] = np.median(nm)
                    else:
                        new_arr[i, j] = imarray[i, j]
        new_im = Image.fromarray(new_arr)
        new_im.save(dst)


src = "E:/正课/大二上/计算机网络/网络编程/图像去噪声/output2/4.jpg"
dst = "E:/正课/大二上/计算机网络/网络编程/图像去噪声/output2/xxx.jpg"

MedianFilter(src, dst)