图像梯度

其他

发布时间 : 2021-01-02 15:20

阅读 :

import cv2 as cv
import numpy as np
from matplotlib import pyplot as plt


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)

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('./lena.jpg')  # blue, green, red
cv.namedWindow('input image', cv.WINDOW_AUTOSIZE)
cv.imshow('input image', src)
# sobel_demo(src)
lapalian_demo(src)
cv.waitKey(0)

cv.destroyAllWindows()

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