图像梯度处理

Sobel算子

import cv2
import numpy as np
img=cv2.imread('../res/pie.png',cv2.IMREAD_GRAYSCALE)
cv2.imshow("img",img)
cv2.waitKey(0)
cv2.destroyAllWindows()

原始图像：

def cv_show(img,name):
    cv2.imshow(name,img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
 
sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)
cv_show(sobelx,'sobelx')

sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)
sobelx=cv2.convertScaleAbs(sobelx)
cv_show(sobelx,'sobelx')

sobely=cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)
sobely=cv2.convertScaleAbs(sobely)
cv_show(sobely,'sobely')

分别计算x和y，再求和

sobelxy=cv2.addWeighted(sobelx,0.5,sobely,0.5,0)
cv_show(sobelxy,'sobelxy')

img=cv2.imread('../res/lena.jpg',cv2.IMREAD_GRAYSCALE)
sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)
sobelx=cv2.convertScaleAbs(sobelx)
sobely=cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)
sobely=cv2.convertScaleAbs(sobely)
sobelxy=cv2.addWeighted(sobelx,0.5,sobely,0.5,0)
cv_show(sobelxy,'sobelxy')

原始图像：

处理后的图像：

Scharr算子

laplacian算子

不同算子的差异

# 不同算子的差异
img=cv2.imread('../res/lena.jpg',cv2.IMREAD_GRAYSCALE)
sobelx=cv2.Sobel(img,cv2.CV_64F,1,0,ksize=3)
sobely=cv2.Sobel(img,cv2.CV_64F,0,1,ksize=3)
sobelx=cv2.convertScaleAbs(sobelx)
sobely=cv2.convertScaleAbs(sobely)
sobelxy=cv2.addWeighted(sobelx,0.5,sobely,0.5,0)

scharrx=cv2.Scharr(img,cv2.CV_64F,1,0)
scharry=cv2.Scharr(img,cv2.CV_64F,0,1)
scharrx=cv2.convertScaleAbs(scharrx)
scharry=cv2.convertScaleAbs(scharry)
scharrxy=cv2.addWeighted(scharrx,0.5,scharry,0.5,0)

laplacian=cv2.Laplacian(img,cv2.CV_64F)
laplacian=cv2.convertScaleAbs(laplacian)

result=np.hstack((sobelxy,scharrxy,laplacian))
cv_show(result,'result')

代码运行结果：