Mahotas - Median filter

In this article we will see how we can apply median filter to the image in mahotas. The median filter is a non-linear digital filtering technique, often used to remove noise from an image or signal. Such noise reduction is a typical pre-processing step to improve the results of later processing (for example, edge detection on an image).
In this tutorial we will use “lena” image, below is the command to load it. 

mahotas.demos.load('lena')

Below is the lena image 

In order to do this we will use mahotas.median_filter method
Syntax : mahotas.median_filter(img)
Argument : It takes image object as argument
Return : It returns image object  

Note : Input image should be filtered or should be loaded as grey
In order to filter the image we will take the image object which is numpy.ndarray and filter it with the help of indexing, below is the command to do this 

image = image[:, :, 0]

Below is the implementation 

# importing required libraries
import mahotas
import mahotas.demos
from pylab import gray, imshow, show
import numpy as np
import matplotlib.pyplot as plt
  
# loading image
img = mahotas.demos.load('lena')
  
# filtering image
img = img.max(2)

print("Image")
  
# showing image
imshow(img)
show()

# applying median filter
new_img = mahotas.median_filter(img)
 

# showing image
print("Median Filter")
imshow(new_img)
show()

Output :

Image

Median Filter

Another example 

# importing required libraries
import mahotas
import numpy as np
from pylab import gray, imshow, show
import os
import matplotlib.pyplot as plt
 
# loading image
img = mahotas.imread('dog_image.png')


# filtering image
img = img[:, :, 0]
  
print("Image")
  
# showing image
imshow(img)
show()

# applying median filter
new_img = mahotas.median_filter(img)
 

# showing image
print("Median Filter")
imshow(new_img)
show()

Output :

Image

Median Filter