Python-openCV高斯平滑
阿新 • • 發佈:2019-02-05
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()