Image Processing Reference
In-Depth Information
∈ℜ ( ) is a relation, T 1 and T 2 are two t -norms, and n and m are two
values with n ≤ ( P − 1)/2 and n ≤ ( Q − 1)/2, then the lower constructor using
T 1 and T 2 may be defined as
If RXY
m
n
LRxy TTRx iyjRxy
, [ (,)
=
( (( )(
), (,))), (,)
xy
∈∈ XY
(8.7)
TT
12
12
i n
j m
=−
=−
where the values of i and j are such that 0 ≤ x i P − 1 and 0 ≤ y i Q − 1.
The values of n and m indicate that the window size is (2 n + 1) × (2 m + 1)
which is centred at ( x , y ). An example on how the lower constructor operation
works is shown. Considering n = m = 1 with window size 3 × 3, T 1 = T 2 = T M
(min t -norm by Zadeh), the value at ( x 1 , y 1 ) is computed as
(0, 0)
0.67
(0, 1)
0.77
(1, 0)
0.74
(1, 1)
0.78
( x − 1, y − 1)
0.76
( x − 1, y )
0.56
( x − 1, y + 1)
0.51
( x , y − 1)
0.78
( x , y )
0.81
( x , y + 1)
0.88
( x + 1, y − 1)
0.62
( x + 1, y )
0.56
( x + 1, y + 1)
0.54
1
L Rxy
T M , [ (,)min(min(. ,. ),(. ,. ),(. ,. )
=
076081 056081 051081
, , (. ,. ),
078081
(. ,. ),(. ,. ),(. ,. ),(. ,.
081081 088081 062081 056081 054081
),(. ,. ))
=
051
.
In this way, the values at each coordinate are computed by shifting the
window point by point and a matrix is formed. One may use different
t -norms for T 1 and T 2 . It is to be noted that on applying the lower con-
structor, the value of R is reduced. The lower constructor darkens the
image as it takes lower values (shown in the example). The smaller the
t -norm, the more reduction in the intensity of the pixels, thereby darken-
ing the image.
Likewise, for the upper constructor, to-conorm is used.
A t -conorm, S : [0, 1] 2 → [0, 1], is an increasing function such that S (0, x ) = x
for all x ∈ [0, 1]. The three basic t -conorms are as follows:
1. The maximum t -conorm by Zadeh, S M ( x , y ) = max( x , y )
2. The product t -conorm by Bandler and Kohout, S P ( x , y ) = x + y x y
3. Lukasiewicz t -conorm, S L ( x , y ) = min( x + y , 1)
Search WWH ::




Custom Search