| Image
Processing Articles
Index |
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| Brief
Description |
| Mean
filtering is a simple,
intuitive and easy
to implement method
of smoothing images,
i.e. reducing the
amount of intensity
variation between
one pixel and the
next. It is often
used to reduce noise
in images. Mean Filter
is the most common
of all the filtering
techniques. |
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| How
It Works |
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| The
idea of mean filtering
is simply to replace
each pixel value in
an image with the
mean (`average') value
of its neighbors,
including itself.
This has the effect
of eliminating pixel
values which are unrepresentative
of their surroundings.
Mean filtering is
usually thought of
as a convolution filter.
Like other convolutions
it is based around
a kernel, which represents
the shape and size
of the neighborhood
to be sampled when
calculating the mean.
Often a 3×3 square
kernel is used, as
shown in Figure 1,
although larger kernels
(e.g. 5×5 squares)
can be used for more
severe smoothing.
(Note that a small
kernel can be applied
more than once in
order to produce a
similar but not identical
effect as a single
pass with a large
kernel.) |
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| Computing
the straightforward
convolution of an
image with this kernel
carries out the mean
filtering process. |
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| Common
Variants |
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| Variations
on the mean smoothing
filter discussed here
include Threshold
Averaging wherein
smoothing is applied
subject to the condition
that the center pixel
value is changed only
if the difference
between its original
value and the average
value is greater than
a preset threshold.
This has the effect
that noise is smoothed
with a less dramatic
loss in image detail. |
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| Other
convolution filters
that do not calculate
the mean of a neighborhood
are also often used
for smoothing. One
of the most common
of these is the Gaussian
smoothing filter. |
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| Basic
Working: |
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| The
effect of a mean Filter
on the Image: |
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| The
result after convolution
is as: |
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| Sample
Project |
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| The
GUI of the whole Project
is as: |
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| The
project is a part
of the series of the
image processing articles
written just for the
prosperity and help
for the students searching
for Image Processing
free stuff. |
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| Image
Processing Articles
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