# Mahotas – Rank Filter

• Last Updated : 10 Jul, 2020

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.

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`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

 `# 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()`

Output :

`Image` `Rank 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 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()`

Output :

`Image` `Rank Filter` My Personal Notes arrow_drop_up