The document discusses different types of mean filters and order statistics filters used for noise reduction in images. It describes four types of mean filters: arithmetic, geometric, harmonic, and contraharmonic. The arithmetic mean filter computes the average value within a window. The geometric mean filter takes the product of pixels within a window. The harmonic mean filter calculates the inverse average of inverse pixel values. The contraharmonic mean filter uses a parameter to reduce salt and pepper noise. Order statistics filters like the median filter replace pixel values with the median within a window, effectively reducing noise.

1. V.SAKTHIPRIYA
II-MSC (IT)
NADAR SARASWATHI COLLEGE OF ARTS
AND SCIENCE

2.  The mean filters is a simple sliding window
spatial filter that replaces the center values
in the window with the average (mean) of all
pixel values in the window.
 The mean filters use the noise reduction
spatial filters.

3.  The mean filter can be divide the four types
of filters. these are .,
 Arithmetic mean filter
 Geometric mean filter
 Harmonic mean filter
 Contraharmonic mean filter

4. Contraharmonic
mean filter
Harmonic mean
filter
Arithmetic
mean filter
Geometric
mean filter
Mean filters

5.  Arithmetic mean filter is the simplest of the
mean filters.let Sxy represent the set of
coordinates in a rectangular sub image
window of size Mxn.centered at point (x,y).
 The arithmetic mean filtering process
computes the average value of the
corrupted image g(x,y)in the area defined by
Sxy.

6. Ỷ(x,y)=1/minƸ(s,t)ƸSxy
g(s,t).
 this operation can be implemented using
convolution method.
 the convolution method is the
mathematical function operates on two
function that produce third function .mean
filter simply smoothes local variable in an
image.
 Noise is reduced as a result of blurring.

7.  Restored pixel is given by the product of the
pixels on the sub image window.
 Geometric mean filter achieve smoothing
comparable to the arithmetic mean filters
f^(x,y)=[π
(s,t)+sxy
g(s,t)]1/min

8.  The harmonic mean filter operation is given
b the expression :
f^(x,y)=min/Σ
(s,t)Σsxy
1/g(s,t)
 The harmonic mean filter work on salt noise
but fails for pepper noise.

9.  The contra harmonic mean filter operation a
restored image based on the expression:
f^(x,y)=Σ
(s,t)Σsxy
g(s,t)q+1
Σ
(s,t)Σsxy
g(s,t)q
 Q is called as the filter. This filter reduced
eliminating the effects of salt and pepper
noise.postive value eliminate the pepper
noise.for negative value eliminate the salt noise.

10.  Order statistics filter are spatial filter whose
response is based on ordering the value of
pixel contained in image are encompassed by
filters.
median filter
max and min filter
mid point filtering

11.  Order statistics filter is the median
filter,replace the value of a pixel by median
of the gray level neighborhood of that pixel.
 Median filter gives excellent result of
corrupted image.its compare the value.

12.  Replace the value of a pixel by the median of
pixel values and work well with various types
of noise.
f^(x,y)=median
(s,t)Σsxy
{ g(s,t)}.

13.  Median filter is most used in image processing.it
is by no means the only one.the median
represents the 50th percentile of a ranked set of
numbers.
 It reduce the pepper noise finding brighter
pointer.
f^(x,y)=max
(s,t)Σsxy
{ g(s,t)}.
f^(x,y)=min
(s,t)Σsxy
{ g(s,t)}.

14.  Mid point filter simply computes the mid
point between the maximun and minimum
values in the area by the filters.
f^(x,y)=1/2[max
(s,t)Σsxy
{ g(s,t)}+ min
(s,t)Σsxy
{ g(s,t)}]
 Filter combine order statistics and
averageing.it works randomly distributed
noise.

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