Mahotas – Rank Filter

In this article we will see how we can apply rank filter on image in mahotas. The rank filter, especially filters isolated pixels out, whose intensity differs greatly from that of its immediate neighborhood. Large areas with constant intensity values adjacent to these pixels, as well as edges, are retained after this filter has been used.

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.rank_filter method

Syntax : mahotas.rank_filter(img, neighbour, rank)



Argument : It takes image object and two integer 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

filter_none

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# importing required libraries
import mahotas
import mahotas.demos
from pylab import gray, imshow, show
import numpy as np
import matplotlib.pyplot as plt
    
# loading iamge
img = mahotas.demos.load('lena')
    
# filtering image
img = img.max(2)
  
print("Image")
    
# showing image
imshow(img)
show()
  
# neighbour pixel
neighbour = 3
  
# rank
rank = 2
  
# applaying rank filter
new_img = mahotas.rank_filter(img, neighbour, rank)
   
  
# showing image
print("Rank Filter")
imshow(new_img)
show()

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Output :

Image

Rank Filter

Another example

filter_none

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code

# importing required libraries
import mahotas
import numpy as np
from pylab import gray, imshow, show
import os
import matplotlib.pyplot as plt
   
# loading iamge
img = mahotas.imread('dog_image.png')
  
  
# fltering image
img = img[:, :, 0]
    
print("Image")
    
# showing image
imshow(img)
show()
  
# neighbour pixel
neighbour = 3
  
# rank
rank = 2
  
# applaying rank filter
new_img = mahotas.rank_filter(img, neighbour, rank)
   
  
# showing image
print("Rank Filter")
imshow(new_img)
show()

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Output :

Image

Rank Filter

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