网站建设策划文案,网站设计说明书,凡科建站步骤,百度收录快的发帖网站一、两种算子
一阶导数—Sobel算子
水平梯度#xff1a;
垂直梯度#xff1a;
最终图像梯度#xff1a;
二阶导数—Laplacian算子
在二阶导数的时候#xff0c;最大变化处的值为零#xff0c;即边缘是零值。 常见的拉普拉斯算子#xff1a;、其所有元素之和为零。…一、两种算子
一阶导数—Sobel算子
水平梯度
垂直梯度
最终图像梯度
二阶导数—Laplacian算子
在二阶导数的时候最大变化处的值为零即边缘是零值。 常见的拉普拉斯算子、其所有元素之和为零。
二、Sobel算子
cv2.Sobel(image,cv2.CV_32F,1,0)image为代求的图像CV_32F为图像的深度(32为float类型)255肯定不够故选择大点 cv2.convertScaleAbs(grad_x)将计算出来的正负数全部转换为正值然后转换到8位的图像上去
import cv2
import numpy as np
from matplotlib import pyplot as pltdef sobel(image):grad_x cv2.Sobel(image,cv2.CV_32F,1,0)grad_y cv2.Sobel(image,cv2.CV_32F,0,1)gradx cv2.convertScaleAbs(grad_x)grady cv2.convertScaleAbs(grad_y)cv2.imshow(gradient-x,gradx)cv2.imshow(gradient-y,grady)gradxy cv2.addWeighted(gradx,0.5,grady,0.5,0)cv2.imshow(gradient,gradxy)src cv2.imread(rG:\Juptyer_workspace\study\opencv\opencv3\a1.jpg)
cv2.imshow(image,src)
cv2.namedWindow(image,cv2.WINDOW_AUTOSIZE)
sobel(src)cv2.waitKey(0)
cv2.destroyAllWindows()效果图如下
三、Scharr算子(Sobel算子的增强版)但对噪声更加敏感
import cv2
import numpy as np
from matplotlib import pyplot as pltdef sobel(image):grad_x cv2.Scharr(image,cv2.CV_32F,1,0)grad_y cv2.Scharr(image,cv2.CV_32F,0,1)gradx cv2.convertScaleAbs(grad_x)grady cv2.convertScaleAbs(grad_y)cv2.imshow(gradient-x,gradx)cv2.imshow(gradient-y,grady)gradxy cv2.addWeighted(gradx,0.5,grady,0.5,0)cv2.imshow(gradient,gradxy)src cv2.imread(rG:\Juptyer_workspace\study\opencv\opencv3\a1.jpg)
cv2.imshow(image,src)
cv2.namedWindow(image,cv2.WINDOW_AUTOSIZE)
sobel(src)cv2.waitKey(0)
cv2.destroyAllWindows()效果图如下
四、Laplacian算子(直接调用API)
import cv2
import numpy as np
from matplotlib import pyplot as pltdef lapalian(image):dst cv2.Laplacian(image,cv2.CV_32F)lpls cv2.convertScaleAbs(dst)cv2.imshow(lapalian,lpls)src cv2.imread(rG:\Juptyer_workspace\study\opencv\opencv3\a1.jpg)
cv2.imshow(image,src)
cv2.namedWindow(image,cv2.WINDOW_AUTOSIZE)
lapalian(src)cv2.waitKey(0)
cv2.destroyAllWindows()效果图如下
五、Laplacian算子(自定义卷积核)
import cv2
import numpy as np
from matplotlib import pyplot as pltdef lapalian(image):#kernel np.array([[1,1,1],[1,-8,1],[1,1,1]])kernel np.array([[0,1,0],[1,-4,1],[0,1,0]])dst cv2.filter2D(image,cv2.CV_32F,kernelkernel)lpls cv2.convertScaleAbs(dst)cv2.imshow(lapalian,lpls)src cv2.imread(rG:\Juptyer_workspace\study\opencv\opencv3\a1.jpg)
cv2.imshow(image,src)
cv2.namedWindow(image,cv2.WINDOW_AUTOSIZE)
lapalian(src)cv2.waitKey(0)
cv2.destroyAllWindows()效果图如下
