5-1感觉这些方法主体都差不多，就是微分算子不同，懒得一个个写了
from cv2 import cv2 import numpy as np import random def singleDirectionsharpen(img, N=3): p = N // 2 img_shape = np.shape(img) out = np.zeros(img_shape) for i in range(img_shape[0]): for j in range(img_shape[1]): if i >= p and i < img_shape[0] - p and j >= p and j < img_shape[1] - p: out[i][j] = img[i - 1][j - 1] - img[i + 1][j - 1] + 2 * (img[i - 1][j] - img[i + 1][j]) + img[i - 1][j + 1] - img[i + 1][j + 1] else: out[i][j] = 0 return out img = cv2.imread("C:\\test\\1.jpg") gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) single_irection_sharpen = singleDirectionsharpen(gray) cv2.imwrite("C:\\test\\single_irection_sharpen.jpg", single_irection_sharpen) single_irection_sharpen = cv2.imread("C:\\test\\single_irection_sharpen.jpg") cv2.imshow('gray', gray) cv2.imshow('single_irection_sharpen', single_irection_sharpen) cv2.waitKey() cv2.destroyAllWindows