Image Processing Basics - Digital Signal Processing: Fundamentals and Applications - page 694

Table 14.2 Image Equalization in Example 14.5.
Pixel pðm; nÞ Number of

Pixels

Number of Pixels
£ pðm; nÞ

Equalized
Pixel Level Level

0 2 2 1

1 7 9 3

2 5 14 5

3 3 17 6

4 1 18 6

5 1 19 7

6 1 20 7

7 0 20 7

Perform equalization using the histogram in Example 14.4, and plot the histogram for the equalized image.
Solution:
Using the histogram result in Table 14.1 , we can compute an accumulative count for each grayscale level as shown
in Table 14.2 . The equalized pixel level using Equation (14.5) is given in the last column.
To see how the old pixel level pðm; nÞ¼4 is equalized to the new pixel level p eq ðm; nÞ¼6, we apply
Equation (14.5) :

p eq m; n ¼ round 18

20 7

¼ 6

The equalized image using Table 14.2 is finally obtained by replacing each old pixel value in the old image with its
corresponding equalized new pixel value:

2
4

3
5

13557
53353
36666
15733

To see how the histogram is changed, we compute the pixel level counts according to the equalized image. The
result is given in Table 14.3 , and Figure 14.12 shows the new histogram for the equalized image.

Table 14.3 Pixel Level Distribution Counts of the Equalized Image in Example 14.5
Pixel pðm; nÞ Level Number of Pixels

0 0

1 2

2 0

3 6

4 0

5 5

6 4

7 2