1.過濾圖片中的噪聲

import cv2
import numpy as np
import matplotlib.pyplot as plt

img = cv2.imread('./01.jpg', 0)  # 直接讀取為灰度影象
img1 = cv2.imread('./01.jpg', 1)
for i in range(2000):
    temp_x = np.random.randint(0, img.shape[0])
    temp_y = np.random.randint(0, img.shape[1])
    img[temp_x][temp_y] = 255
    img1[temp_x][temp_y] = 255
 

blur11 = cv2.GaussianBlur(img, (5, 5), 0)  # 高斯濾波
blur21 = cv2.medianBlur(img, 5)  # 中指濾波
blur12 = cv2.GaussianBlur(img1, (5, 5), 0)
blur22 = cv2.medianBlur(img1, 5)



plt.subplot(2, 3, 1)
plt.imshow(img, 'gray')  # 預設顏色，另一種為'bgr'
plt.subplot(2, 3, 2)
plt.imshow(blur11, 'gray')  # 預設顏色，另一種為'bgr'
plt.subplot(2, 3, 3)
 
plt.imshow(blur21, 'gray')  # 預設顏色，另一種為'bgr'

plt.subplot(2, 3, 4)
plt.imshow(img1, 'brg')  
plt.subplot(2, 3, 5)
plt.imshow(blur12, 'brg')  
plt.subplot(2, 3, 6)
plt.imshow(blur22, 'brg') 
plt.show()

2.邊緣檢測

import numpy as np
import cv2 as cv
import matplotlib.pyplot as plt

img = cv.imread('./02.jpg', 0)
laplacian = cv.Laplacian(img, cv.CV_64F)  # 拉普拉斯運算元
 
sobelx = cv.Sobel(img, cv.CV_64F, 1, 0, ksize=5)  # sobel運算元是一種常用的邊緣檢測運算元
sobely = cv.Sobel(img, cv.CV_64F, 0, 1, ksize=5)
plt.subplot(2, 2, 1)
plt.imshow(img, cmap='gray')
plt.title('Original')
plt.xticks([])
plt.yticks([])

plt.subplot(2, 2, 2)
plt.imshow(laplacian, cmap='gray')
plt.title('Laplacian')
plt.xticks([])
plt.yticks([])

plt.subplot(2, 2, 3)
plt.imshow(sobelx, cmap='gray')
plt.title('SabelX')
plt.xticks([])
plt.yticks([])

plt.subplot(2, 2, 4)
plt.imshow(sobely, cmap='gray')
plt.title('SabelY')
plt.xticks([])
plt.yticks([])

plt.show()

3.快速傅立葉變化

import cv2
import numpy as np
import matplotlib.pyplot as plt

# 快速傅立葉變換 時空=> 頻率

img = cv2.imread('./02.jpg', 0)
f = np.fft.fft2(img)
fshift = np.fft.fftshift(f)
megnitude_spectrun = 20 * np.log(np.abs(fshift))

plt.subplot(1, 2, 1)
plt.imshow(img, cmap='gray')
plt.title('Inpute Image')
plt.xticks()
plt.yticks()


plt.subplot(1, 2, 2)
plt.imshow(megnitude_spectrun, cmap='gray')
plt.title('Output Image')
plt.xticks()
plt.yticks()

plt.show()

4.圖片直方圖均衡化

import numpy as np
import matplotlib.pyplot as plt
import cv2

img = cv2.imread('./03.jpg', 0)
res = cv2.equalizeHist(img)  # 直方圖均衡化

clahe = cv2.createCLAHE(clipLimit=2, tileGridSize=(10, 10))  # 生成自適應均衡化影象
cl1 = clahe.apply(img)

plt.subplot(1, 3, 1)
plt.imshow(img, 'gray')
plt.subplot(1, 3, 2)
plt.imshow(res, 'gray')
plt.subplot(1, 3, 3)
plt.imshow(cl1, 'gray')

plt.show()