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156 INTELLIGENT COMMUNICATION SYSTEMS
( i ~ l , 7 - l ) ^22^1 (i+1,7-D
0"~ 1, 7) (', 7) (i+1,7)
7
(i-1,7+D i 0', + D i (i+1,7+D
FIGURE 12.7 3 x 3 region for smoothing.
12.3.1 Space Filtering
This method has the following objectives: (1) to eliminate noise from the source
image, called smoothing, and (2) to detect features of the image such as contour
and direction from the source image. To achieve these objectives we use the
Laplacian and gradient operations.
When it is difficult to obtain gray-level values accurately because a high fre-
quency has been introduced into the video signal, a smoothing operation is per-
formed, A mean value is calculated for nine pixels, from pixel (i - 1, j - 1) to pixel
(/ + 1, j + 1), and this value is assigned to a new gray level (see Figure 12.7). The
formula is as follows:
where T(i,f) is the coefficient of g(i,j). This means that f(i, f) is the summation
from g(i-l,j-l) to g(i + lj+i) divided by 9. The gray-level values g(i -IJ-1),
g(ij - 1), g(i +IJ- 1), g(i - I,/), g(i + I,/), g(i - 1,7 + 1), gdJ + 1), gd +1,7 + 1)
are used to calculate/(i, 7) in space filtering.
In space filtering, a mean value is used for/(/,/). Another method involves
decreasing the value of the coefficient as the distance from g(i, j) increases. One
example is shown in Eq. (7).
In general, T(i,j) is described as follows:
Here, w n is the coefficient of the gray level.