数学之路-python计算实战(15)-机器视觉-滤波去噪(归一化块滤波)

Blurs an image using the normalized box filter.

C++: void blur(InputArray src, OutputArray dst, Size ksize, Pointanchor=Point(-1,-1), int borderType=BORDER_DEFAULT )

Python: cv2.blur(src, ksize[, dst[, anchor[, borderType]]]) → dst

Parameters:

src – input image; it can have any number of channels, which are processed independently, but the depth should be CV_8U, CV_16U,CV_16S, CV_32F or CV_64F. dst – output image of the same size and type as src. ksize – blurring kernel size. anchor – anchor point; default value Point(-1,-1) means that the anchor is at the kernel center. borderType – border mode used to extrapolate pixels outside of the image.

注意，blur函数使用了第1个脉冲响应函数，例如以下：

The function smoothes an image using the kernel:

# -*- coding: utf-8 -*-   
#code:myhaspl@myhaspl.com
#归一化块滤波
import cv2
import numpy as np
fn="test3.jpg"
myimg=cv2.imread(fn)
img=cv2.cvtColor(myimg,cv2.COLOR_BGR2GRAY)

#加上椒盐噪声
#灰阶范围
w=img.shape[1]
h=img.shape[0]
newimg=np.array(img)
#噪声点数量
noisecount=100000
for k in xrange(0,noisecount):
    xi=int(np.random.uniform(0,newimg.shape[1]))
    xj=int(np.random.uniform(0,newimg.shape[0]))
    newimg[xj,xi]=255


#滤波去噪
lbimg=cv2.blur(newimg,(5,5))
cv2.imshow(‘src‘,newimg)
cv2.imshow(‘dst‘,lbimg)
cv2.waitKey()
cv2.destroyAllWindows() 

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http://blog.csdn.net/myhaspl/