a morphological approach to remove salt and pepper noise in images

Aravinth Chinnapalanichamy et al ,Int.J.Computer Technology & Applications,Vol 3 (6), 1875-1880
ISSN:2229-6093
If f(x, y) =0, first all H values equal to zero are
changed to 1 and then all the other values are
changed to 0. The order in which the values are
changed is important in this case.
If f(x, y) =255, then all the H values equal to 255
are changed to 1 and all the other values are
changed to 0.
3. All the above conditions and change of values are done
only to facilitate finding the connectivity between
pixels. The 4- connectivity between foreground pixels
(value 1) in matrix H is found (i.e.) no of adjacent
pixels (N) connected to the centre pixel is counted.
4. If this number (N) is greater than a particular value,
say A, then the processing pixel is said to be noise free.
If it is less than A, then it is noise. The value A
depends on the mask size. For a mask of size( 2k+1 x
2k+1 ), the minimum no of pixels that should be
connected together so that the centre pixel is noise free
is (k+1)*(2k+1)
f(x, y) = noisefree, N > A
noise, N ≤ A
were N is te maximum no of adjacent pixels connected
to centre pixel based on 4 − connectivity and A =
k + 1 ∗ (2k + 1)
the median of those values are calculated and that median
value replaces f(x, y). The steps of phase 2 is shown in Fig.2
1. For a mask of size (2k+1 x 2k+1), the following values
are extracted.
f ′ = f(x + s, y + t)
were s, t = 0 to 1
2. The values other than 0 and 255 are found in f’. Then
the median of those values is calculated which in turn is
the estimated correct value.
f x, y = med(f ′ f ′ ≠ 0 255
3. If all the values of f’ are either 0 or 255, then the upper
limit of sand t is incremented by 1. If still the function
f’ has no values other than 0 and 255, then the limit is
again incremented by 1 and this increment happens till
K.
f ′ = f(x + s, y + t)
were s, t = 0 to p, p = 0,1, … k
And f x, y = med(f ′ f ′ ≠ 0 255 .
4. PHASE 2- NOISE REMOVAL USING
MEDIAN FILTER OF VARYING MASK
SIZE
Once the pixel has been identified as noise, then it is
replaced with an estimated value of the correct intensity level.
From the G matrix, certain elements are extracted and then
5. EXPERIMENTAL RESULTS
Simulations are done on various standard images at
different noise levels. The performance of this scheme is
measured by using the parameter PSNR and compared with
the PSNR values of other methods and is shown that our
method is superior to other methods.
The standard images chosen for testing are Lena, Boat and
gold hill. All the images are 8 bit gray scale images with size
512x512. The mask size is chosen accordingly to the noise
density level. For instance, while testing with Lena image
corrupted by impulse noise level of 70%, the mask size
chosen is 5x5. This implies that the value of K is 2. Further
while identifying a noisy pixel in sub stage 2, the value of A is
set as 15. While processing a particular pixel of the image, if
IJCTA | Nov-Dec 2012
Available online@www.ijcta.com
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