I try make python program for do median filter. I got this article http://www.programming-techniques.com/2013/02/median-filter-using-c-and-opencv-image.html , so I try to translate that code to python code.
this the code in python
from cv2 import * #Import functions from OpenCV
import cv2
if __name__ == '__main__':
source = cv2.imread("Medianfilterp.png", CV_LOAD_IMAGE_GRAYSCALE)
final = source[:]
for y in range(len(source)):
for x in range(y):
final[y,x]=source[y,x]
members=[source[0,0]]*9
for y in range(1,len(source)-1):
for x in range(1,y-1):
members[0] = source[y-1,x-1]
members[1] = source[y,x-1]
members[2] = source[y+1,x-1]
members[3] = source[y-1,x]
members[4] = source[y,x]
members[5] = source[y+1,x]
members[6] = source[y-1,x+1]
members[7] = source[y,x+1]
members[8] = source[y+1,x+1]
members.sort()
final[y,x]=members[4]
cv.NamedWindow('Source_Picture', cv.CV_WINDOW_AUTOSIZE)
cv.NamedWindow('Final_Picture', cv.CV_WINDOW_AUTOSIZE)
cv2.imshow('Source_Picture', source) #Show the image
cv2.imshow('Final_Picture', final) #Show the image
cv2.waitKey()
This is a picture before the median filter:
but I got strange results, the results of the program :
First, I recommend that you not re-invent the wheel. OpenCV already contains a method to perform median filtering:
final = cv2.medianBlur(source, 3)
That said, the problem with your implementation lies in your iteration bounds. Your y
range is correct. However, for x in range(1,y-1):
only iterates up to the current y
value, and not the entire x
range of the image. This explains why the filter is only applied to a triangular region in the lower-left of the image. You can use the shape
field of the image (which is really just a numpy array) to get the image dimensions, which can then be iterated over:
for y in range(1,source.shape[0]-1):
for x in range(1,source.shape[1]-1):
This will apply the filter to the entire image: