简单卷积

以上用了锐化，只需将如下代码的

cov=np.ones([3,3])/5000
# cov[1,1]=1

改为

cov=（-1）*np.ones([3,3])
cov[1,1]=9
cov=cov/800

如下为简单卷积代码，代码很简单，仔细看将会明白其中含义。我简单说一下，代码思路：读取一幅图，以3通道颜色读取，便获得维度为（300,533,3）的三维矩阵，随后使用3*3的卷积矩阵，依次滑动，即可获得新的（300,533,3）维的新矩阵，而后将其矩阵为图像输出，便获得以上相似先后的图像。import cv2 as cvimport numpy as npv_a=np.zeros([1,533])img=cv.imread('C:\\Users\\HHQ\\Desktop\\tangjun\\3.jpg' ,cv.IMREAD_COLOR)print(img.shape)print(type(img))img=np.array(img)cv.imshow('display image',img)cv.waitKey(0)img0=np.vstack((v_a,img[:,:,0],v_a))img1=np.vstack((v_a,img[:,:,1],v_a))img2=np.vstack((v_a,img[:,:,2],v_a))h_a=np.zeros([302,1])img0=np.hstack((h_a,img0,h_a))img1=np.hstack((h_a,img1,h_a))img2=np.hstack((h_a,img2,h_a))cov=np.ones([3,3])/5000# cov[1,1]=1img_cov0=np.zeros([300,533])img_cov1=np.zeros([300,533])img_cov2=np.zeros([300,533])for i in range(300):    for j in range(533):        img_cov0[i, j] = cov[0, 0] * img0[i + 0, j + 0] + cov[0, 1] * img0[i + 0, j + 1] + cov[0, 2] * img0[            i + 0, j + 2] + cov[1, 0] * img0[i + 1, j + 0] + cov[1, 1] * img0[i + 1, j + 1] + cov[1, 2] * img0[                             i + 1, j + 2] + cov[2, 0] * img0[i + 2, j + 0] + cov[2, 1] * img0[i + 2, j + 1] + cov[                             2, 2] * img0[i + 2, j + 2]        img_cov1[i, j] = cov[0, 0] * img1[i + 0, j + 0] + cov[0, 1] * img1[i + 0, j + 1] + cov[0, 2] * img1[            i + 0, j + 2] + cov[1, 0] * img1[i + 1, j + 0] + cov[1, 1] * img1[i + 1, j + 1] + cov[1, 2] * img1[                             i + 1, j + 2] + cov[2, 0] * img1[i + 2, j + 0] + cov[2, 1] * img1[i + 2, j + 1] + cov[                             2, 2] * img1[i + 2, j + 2]        img_cov2[i, j] = cov[0, 0] * img2[i + 0, j + 0] + cov[0, 1] * img2[i + 0, j + 1] + cov[0, 2] * img2[            i + 0, j + 2] + cov[1, 0] * img2[i + 1, j + 0] + cov[1, 1] * img2[i + 1, j + 1] + cov[1, 2] * img2[                             i + 1, j + 2] + cov[2, 0] * img2[i + 2, j + 0] + cov[2, 1] * img2[i + 2, j + 1] + cov[                             2, 2] * img2[i + 2, j + 2]img_cov=np.zeros([300,533,3])img_cov[:,:,0]=img_cov0img_cov[:,:,1]=img_cov1img_cov[:,:,2]=img_cov2# print(img_cov)print(img_cov.shape)cv.imshow('display img_cov',img_cov)cv.waitKey(0)