【【opencv学习笔记学习笔记 19 图像的梯度】图像的梯度】
图像的梯度图像的梯度
一阶导数
二阶导数 —拉普拉斯算子系数和为0
一阶导数一阶导数
import cv2 as cv
import numpy as np
def sobel_demo(image):
#
grad_x = cv.Scharr(image, cv.CV_32F, 1, 0)
grad_y = cv.Scharr(image, cv.CV_32F, 0, 1)
#
gradx = cv.convertScaleAbs(grad_x)
grady = cv.convertScaleAbs(grad_y)
cv.imshow("gradient-x", gradx)
cv.imshow("gradient-y", grady)
gradxy = cv.addWeighted(gradx, 0.5, grady, 0.5, 0)
cv.imshow("gradient", gradxy)
src = cv.imread("image5.jpg")
cv.namedWindow("input image", cv.WINDOW_AUTOSIZE)
cv.imshow("input image", src)
sobel_demo(src)
cv.waitKey(0)
cv.destroyAllWindows()
效果展示效果展示
二级导数二级导数
def lapalian_demo(image):
dst = cv.Laplacian(image, cv.CV_32F)
# 转换
lpls = cv.convertScaleAbs(dst)
cv.imshow("lapalian_demo", lpls)
效果展示效果展示
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