International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 06 Issue: 10 | Oct 2019 www.irjet.net p-ISSN: 2395-0072
© 2019, IRJET | Impact Factor value: 7.34 | ISO 9001:2008 Certified Journal | Page 841
Image Restoration using Adaptive Median Filtering
Hetvi Soni
[1]
, Darshana Sankhe
[2]
Student
[1]
, Professor
[2]
, Dept. Of Electronics Engineering, D.J Sanghvi College of Engineering, Mumbai, India
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Abstract – In the field of image processing, image
restoration is the most essential task. Image often gets
corrupted due to which there is presence of noise in the
image. Generally median filter is used to remove the
presence of such noise but median filter works fine for
about intensity of 20% noise in the image. So in order
to get a better image restoration we can use another
image restoration technique which is adaptive median
filtering which works very well for noise intensity
beyond 20% .The benefit of adaptive filter over median
filter is that it does not erode away edges or small
details in the image.
Key Words: Adaptive median filter, Image
Processing, Median filter, Salt and Pepper Noise,
Gaussian Noise PSNR.
1. INTRODUCTION
In the field of image processing image gets corrupted
during image transmission or acquisition stage due
to various influencing parameters such as faulty
device etc. Such type of corruption gives rise to noise
in the image which affects the information present in
the image. The various type of noise that arises in the
image is impulse noise also know as salt and pepper
noise, Gaussian noise, and speckle noise to name a
few [1].
In order to retrieve the original information from the
image and eliminate noise from the image we need to
apply certain de-noising techniques. These de-
noising techniques make use of kernel which is made
to convolve over the image and the result obtain
through this convolution is a noise free image. The
size of kernel (window) used for the same varies and
intended output with same also varies.
One such commonly used technique is median
filtering. Median filtering works fine when the noise
intensity is less but it starts to fail when the noise
intensity in the image is high [3].
In order to overcome this problem we can make of
spatial filtering technique. One such Filtering
algorithm used is adaptive median filter. Adaptive
median filtering is better than median as it is a two
step filtering technique. The main advantage of
adaptive median filter is that the behavior of the
adaptive filter changes depending on the
characteristics of the image under filter. Other main
feature of adaptive filter is that it works well not only
for impulse noise but also for speckle noise and
Gaussian noise [3].
2. MEDIAN FILTER
Median filter is the most commonly used filter. It
is a non linear method of filtering. The size of the
kernel can be of nxn size which is made to convolve
or slide over a mxm corrupted image. While
performing this operation the median value of nxn
kernel on the image is obtained and then the value of
a particular pixel is replaced with the median value
of the nxn kernel.
Fig -1: Sorting in median filter.
2.1. Drawbacks of median filter:
Effective only when the noise is impulse
noise (salt and pepper).
Its output quality deteriorates when the
noise is more than 20%.
It does not work efficiently when the
spatial density of noise is high.
For large kernel size, there is no proper
smoothening of the image instead
valuable information from the image
gets blur.
