Images noisy images is a vital problem nowadays. The

Images
are vital and convenient for communication. As the rapid development of imaging
technique and mobile devices, numerous images are produced, translated and
edited everyday. However, as the variety of imaging devices, the quality of images
is unstable. For example, cameras on mobile usually produce images with noise,
blurry or other spotsinevitably. Some information may be damaged during the
transition process between different devices. Thus, to remove noise and recover
meaningful information from noisy images is a vital problem nowadays. The
causes of noise in images are flaws in data transmission, imperfect optics,
sensor malfunctioning, processing techniques and electronic interference.

 Noise is the most annoying problem in
processing. Noise introduces random variations into image that fluctuate the original
values to some different values. One way to get rid of this problem is the
development of such a robust algorithm that can perform the processing tasks in
presence of noise. The other way is to design a filtration process to eliminate
the noise from images while preserving its features, edges and details. Filters
are better option to remove the noise from the image because their implementation
is very easy.There are various filters which can remove the noise from images
and preserve image details.. The filters can be divided in two types: linear
filter and non-linear filter. Linear filters are like average filter or called
averaging low pass filter. But linear filter tends to blur edges and other
details of image, which may reduce the accuracy of output. On the other hand
non-linear type filter like median filter has better results than linear filter
because median filter remove the impulse noise without edge blurring. A median
filter is an example of a non-linear filter and it is very good at preserving
image detail. The standard median filter mostly used because of its good
performance and preservation of image details. Generally different filters are
used for eliminating different noises like Mean filter is used to remove the
impulse noise. Median filtering is a nonlinear operation used in image
processing to salt and pepper noise. Weiner filter is to filter out noise that
has corrupted a signal.

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The
following three steps are used to calculate median:1. Process every pixel in
the image one by one.2. Select the size of filtering window and sort the all
pixels of window in order based upon their intensities.3. Replace the central
pixel with the median value of sorted pixels.

The
performance of median filter also depends on the size of window of filter.
Smaller window preserves the details but it will cause the reduction in noise
suppression. Larger window has great noise reduction capability but image
details (edges, corners, fine lines) preservation is limited. With the
improvement in the standard median filters, there were so many filters has designed
like weighted median filter, centre weighted median filter ,adaptive median
filter, rank order median filter and many other improved filters. Different median
filters uses different sorting algorithm like merge sort, quick sort, heap sort
to sort the elements of window. Some techniques focused on noise detection, so
there are different techniques to find out that the pixel is noisy or noiseless,
so that only noisy pixel will be replaced by the median value and noiseless
pixel will be unaffected. These techniques reduce the processing time and also
improve the quality of image.It is based on a statistical approach.

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