OpenCV-阈值与平滑处理

 阈值处理与平滑处理都是去除图片中的“杂质”，让图片更加的干净明了。“杂质”去除后的图片处理会更加的准确。下面是阈值与平滑处理的概念介绍。

阈值处理基本概念

下面为代码以及处理效果

import cv2
import numpy as np
peppa = cv2.imread('peppa.jpg')
img=cv2.cvtColor(peppa,cv2.COLOR_BGR2GRAY)
cv2.imshow('Peppa',img)
ret,thresh1 = cv2.threshold(img,200,255,cv2.THRESH_BINARY)
ret,thresh2 = cv2.threshold(img,200,255,cv2.THRESH_BINARY_INV)
ret,thresh3 = cv2.threshold(img,200,255,cv2.THRESH_TRUNC)
ret,thresh4 = cv2.threshold(img,200,255,cv2.THRESH_TOZERO)
ret,thresh5 = cv2.threshold(img,200,255,cv2.THRESH_TOZERO_INV)
cv2.imshow('BINARY',thresh1)
cv2.imshow('BINARY_INV',thresh2)
cv2.imshow('TRUNC',thresh3)
cv2.imshow('TOZERO',thresh4)
cv2.imshow('TOZERO_INV',thresh5)
peppa_body=cv2.bitwise_and(peppa,peppa,mask=thresh2)
cv2.imshow('peppa_body',peppa_body)
cv2.waitKey()
cv2.destroyAllWindows()

平滑处理

 均值滤波

 方框滤波

高斯滤波

3.4中值滤波

双边滤波

2D卷积

案例@ Fu Xianjun. All Rights Reserved.