14_Sobel算子、Scharr算子与Laplacian算子

# Sobel算子、Scharr算子与Laplacian算子
# 1. Sobel算子

# 1.1 圆形处理(例)
import cv2  # opencv的缩写为cv2
import matplotlib.pyplot as plt  # matplotlib库用于绘图展示
import numpy as np  # numpy数值计算工具包


pie = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/06_pie.png')  # 读取图像
cv2.imshow('img', pie)
cv2.waitKey()
cv2.destroyAllWindows()


# 梯度就是边界点，左边右边不一样
def cv_show(img, name):
    cv2.imshow(name, img)
    cv2.waitKey()
    cv2.destroyAllWindows()


# 白到黑是正数，黑到白是负数了，所有的负数会被截断成 0，所以要取绝对值
sobelx = cv2.Sobel(pie, cv2.CV_64F, 1, 0, ksize=3)  # 1,0 表示只算水平方向梯度
cv_show(sobelx, 'sobelx')

sobelx = cv2.Sobel(pie, cv2.CV_64F, 1, 0, ksize=3)
sobelx = cv2.convertScaleAbs(sobelx)  # 取负数时，取绝对值
cv_show(sobelx, 'sobelx')

sobely = cv2.Sobel(pie, cv2.CV_64F, 0, 1, ksize=3)  # 1,0 只算 y 方向梯度
sobely = cv2.convertScaleAbs(sobely)  # 取负数时，取绝对值
cv_show(sobely, 'sobely')

# 计算 x 和 y 后，再求和
sobelxy = cv2.addWeighted(sobelx, 0.5, sobely, 0.5, 0)  # 0是偏置项
cv_show(sobelxy, 'sobelxy')

# 不建议直接计算,还有重影
sobelxy = cv2.Sobel(pie, cv2.CV_64F, 1, 1, ksize=3)
sobelxy = cv2.convertScaleAbs(sobelxy)
cv_show(sobelxy, 'sobelxy')

# 1.2 人照处理(例)

img = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/07_Lena.jpg', cv2.IMREAD_GRAYSCALE)
cv_show(img, 'img')

img = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/07_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)

img1 = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/07_Lena.jpg', cv2.IMREAD_GRAYSCALE)
sobelxy1 = cv2.Sobel(img, cv2.CV_64F, 1, 1, ksize=3)
sobelxy1 = cv2.convertScaleAbs(sobelxy1)
res = np.hstack((sobelxy, sobelxy1))
cv_show(res, 'sobelxy')

# 整体计算有重影和模糊，不建议整体计算
img = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/07_Lena.jpg', cv2.IMREAD_GRAYSCALE)
sobelxy = cv2.Sobel(img, cv2.CV_64F, 1, 1, ksize=3)
sobelxy = cv2.convertScaleAbs(sobelxy)
cv_show(sobelxy, 'sobelxy')

# 2. Scharr算子
# 3. Laplacian算子

# 4. 各个算子区别

img = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/07_Lena.jpg', cv2.IMREAD_GRAYSCALE)
cv_show(img, 'img')

# 不同算子的差异
img = cv2.imread('D:/pycharm/pycharm-cope/opencv/resource/photo/07_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)  # 没有 x、y，因为是求周围点的比较
laplacian = cv2.convertScaleAbs(laplacian)

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

 结果展示