Image Enhancement - Medical Image Processing: Advanced Fuzzy Set Theoretic Techniques - page 92

(a) (b)

FIGURE 5.4
(a) Blood vessel image and (b) enhancement using the IF method (method I).

Finally, the image in the grey-level domain is written as

gL ʹ=− ( 1 μ α ) g

DA
opt pt

()

( )

_

and

(5.8)

μ () g =+− α αμ λανλ ( 1 ) (; ) g − ( ; g )

DA ( ) opt opt A opt optA opt

α IFSopt _

g and g ′ are the initial and final intensity levels of the image, respectively.

Example 5.2
An example of a medical image using the IF method by Vlachos is shown
in Figure 5.4 to illustrate the efficacy of the method. Entropy by Vlachos
and Sergiadis is used in the enhancement method.

5.4.2 Two-Dimensional Entropy-Based Intuitionistic
Fuzzy Enhancement (Method II)

The 2D entropy-based IF enhancement is suggested by Vlachos and Sergiadis
[19] where they used two parameters instead of one. The image is fuzzified
with the membership function μ A ( g ) using Equation 5.1.
Using Yager's fuzzy complement, the membership function of the IF image
( A ) is given as

( )

1 / ω

(5.9)

IFS ω

μ ω μ (;) g =− 1 ( ) g , ω > 0

A A

and the non-membership function is generated as

= (

) =− (

() /

)

λω

IFS IFS

μ ω ν ωλϕμ ωλ (;,) g (;,) g 1 g (5.10)

A A A