opencv-python 图像基础处理（二）

图像阈值

ret, dst = cv2.threshold(src, thresh, maxval, type)

- src： 输入图，只能输入单通道图像，通常来说为灰度图
- dst： 输出图
- thresh： 阈值 0-255 一般是127
- maxval： 当像素值超过了阈值（或者小于阈值，根据type来决定），所赋予的值  最大值255
- type：二值化操作的类型，包含以下5种类型： cv2.THRESH_BINARY； cv2.THRESH_BINARY_INV； cv2.THRESH_TRUNC； cv2.THRESH_TOZERO；cv2.THRESH_TOZERO_INV

- cv2.THRESH_BINARY           超过阈值部分取maxval（最大值），否则取0
- cv2.THRESH_BINARY_INV    THRESH_BINARY的反转
- cv2.THRESH_TRUNC            大于阈值部分设为阈值，否则不变
- cv2.THRESH_TOZERO          大于阈值部分不改变，否则设为0
- cv2.THRESH_TOZERO_INV  THRESH_TOZERO的反转

import cv2
import numpy as np
import matplotlib.pyplot as plt#Matplotlib是RGB
 
img=cv2.imread('d:/image0.jpg')
img_gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
 
ret, thresh1 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)
ret, thresh2 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY_INV)
ret, thresh3 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TRUNC)
ret, thresh4 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO)
ret, thresh5 = cv2.threshold(img_gray, 127, 255, cv2.THRESH_TOZERO_INV)
 
titles = ['Original Image', 'BINARY', 'BINARY_INV', 'TRUNC', 'TOZERO', 'TOZERO_INV']
images = [img, thresh1, thresh2, thresh3, thresh4, thresh5]
 
for i in range(6):
    plt.subplot(2, 3, i + 1), plt.imshow(images[i], 'gray')
    plt.title(titles[i])
    plt.xticks([]), plt.yticks([])
plt.show()

滤波处理

import cv2
import numpy as np
import matplotlib.pyplot as plt#Matplotlib是RGB
 
img=cv2.imread('d:/image0.jpg')
#cv2.imshow("image",img)
#均值滤波
bluer=cv2.blur(img,(,))
 
#方框滤波
#基本和均值一样，可以选择归一化
box=cv2.boxFilter(img,-,(,),normalize=True)
 
#方框滤波
#基本和均值一样，可以选择归一化,容易越界
box2=cv2.boxFilter(img,-,(,),normalize=False)

res=np.hstack((bluer,box,box2))
cv2.imshow("da",res)

 cv2.waitKey()
 cv2.destroyAllWindows()

#高斯滤波
#高斯滤波得卷积核里地数值满足高斯分布，相当于中间地分布
import cv2
import numpy as np
img=cv2.imread("d:/image0.jpg")
aussian=cv2.GaussianBlur(img,(3,3),1)

#均值滤波

bluer=cv2.blur(img,(5,5))
#中值滤波
median=cv2.medianBlur(img,5)
 
res=np.hstack((aussian,bluer,median))
cv2.imshow("aussian vs averge",res)
cv2.waitKey(0)
cv2.destroyAllWindows()