對於可分離式卷積核可通過先進行x方向卷積再進行y方向卷積進行影象卷積計算
#coding=utf-8
import cv2
import  numpy as np
from scipy import signal
def gauss_blur(img,sigma,H,W):

    gauss_kenrnel1=cv2.getGaussianKernel(W,sigma,cv2.CV_64F)
    gauss_kenrnel1=np.transpose(gauss_kenrnel1) #轉置
gauss_blur1=signal.convolve2d(img,gauss_kenrnel1,mode
 
='full',boundary='fill',fillvalue=0)
    gauss_kenrnel2 = cv2.getGaussianKernel(H, sigma,cv2.CV_64F)
    gauss_blur2 = signal.convolve2d(gauss_blur1, gauss_kenrnel2, mode='full', boundary='fill', fillvalue=0)
    return gauss_blur2

img=cv2.imread('timg.jpeg',cv2.CV_LOAD_IMAGE_GRAYSCALE)
blur_img=gauss_blur(img,4
 
,5,5)
blur_img=np.round(blur_img)
blur_img=blur_img.astype(np.uint8)
cv2.imshow('img',img)
cv2.imshow('blur_img',blur_img)
cv2.waitKey(0)
cv2.destroyAllWindows()