图像锐化处理

Laplace算子

import cv2 import numpy as np import matplotlib.pyplot as plt img = cv2.imread('img/jy3.jpg') img1 = np.float32(img) #转化数值类型 kernel = np.array([[0, -1, 0], [-1, 5, -1], [0, -1, 0]]) #计算出来会是负数 #np.ones((5,5),np.float32)/25 dst = cv2.filter2D(img1,-1,kernel) #cv2.filter2D(src,dst,kernel,auchor=(-1,-1))函数： #输出图像与输入图像大小相同 #中间的数为-1，输出数值格式的相同plt.figure() plt.subplot(1,2,1),plt.imshow(img1,'gray')#默认彩色，另一种彩色bgr plt.subplot(1,2,2),plt.imshow(dst,'gray') cv2.imshow("dst",dst) cv2.imwrite("ttttt.jpg",dst) cv2.waitKey(0)

Sobel算子

import cv2 import numpy as np img=cv2.imread('img\gsyellow_3.jpg') x=cv2.Sobel(img,cv2.CV_16S,1,0)#对x求导 y=cv2.Sobel(img,cv2.CV_16S,0,1)#对y求导 absX=cv2.convertScaleAbs(x) # 转回uint8 absY=cv2.convertScaleAbs(y) dst = cv2.addWeighted(absX,0.5,absY,0.5,0) cv2.imshow('absX',absX) cv2.imshow('absY',absY) cv2.imshow('Result',dst) cv2.waitKey(0) cv2.destroyAllWindows() #cv2.imwrite('ttttt_sobel1.jpg',absX) #cv2.imwrite('ttttt_sobel2.jpg',absY) #cv2.imwrite('ttttt_sobel3.jpg',dst)

Canny算子

import cv2 import numpy as np img=cv2.imread('img/gsyellow_3.jpg',0) img1=cv2.imread('123.jpg') #为了让结果更清晰，这里的ksize设为3， gray_lap=cv2.Laplacian(img,cv2.CV_16S,ksize=3)#拉式算子 gray_lap1=cv2.Laplacian(img1,cv2.CV_16S,ksize=3) dst=cv2.convertScaleAbs(gray_lap) dst1=cv2.convertScaleAbs(gray_lap1) cv2.imshow('laplacian',dst) cv2.imshow('laplacian1',dst1) cv2.imwrite('ttttt_canny1.jpg',dst) cv2.imwrite('ttttt_canny2.jpg',dst1) cv2.waitKey(0) cv2.destroyAllWindows()