opencv学习（十八）：图像梯度

最新推荐文章于 2024-09-10 22:45:16 发布

小韩学长

最新推荐文章于 2024-09-10 22:45:16 发布

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分类专栏： python3.6+opencv3.4

本文链接：https://blog.youkuaiyun.com/weixin_39036700/article/details/84879446

程序代码：

#导入cv模块
# -*- coding=utf-8 -*-
import cv2 as cv
import numpy as np

#lapalian算子
def lapalian_demo(image):
    # dst=cv.Laplacian(image,cv.CV_32F)
    # lpls=cv.convertScaleAbs(dst)

    kernel=np.array([[1,1,1],[1,-8,1],[1,1,1]])
    dst=cv.filter2D(image,cv.CV_32F,kernel=kernel)
    lpls=cv.convertScaleAbs(dst)
    cv.imshow("lapalian_demo",lpls)

#sobel算子
def sobel_demo(image):
    grad_x=cv.Sobel(image,cv.CV_32F,1,0)
    grad_y=cv.Sobel(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)

#图像梯度：scharr算子：增强边缘
def scharr_image(image):
    grad_x = cv.Scharr(image, cv.CV_32F, 1, 0)#x方向导数
    grad_y = cv.Scharr(image, cv.CV_32F, 0, 1)#y方向导数
    gradx = cv.convertScaleAbs(grad_x)
    grady = cv.convertScaleAbs(grad_y)
    cv.imsho