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[1
-
4]
.
T
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[
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as
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Fi
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1
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Fig
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W
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d
c
o
m
p
r
es
s
io
n
.
O
n
e
o
f
th
e
m
o
s
t
s
ig
n
i
f
ica
n
t
d
eter
m
in
an
ts
f
o
r
ass
e
s
s
i
n
g
th
e
o
p
er
atio
n
o
f
t
h
e
w
ater
m
ar
k
i
n
g
alg
o
r
ith
m
i
s
t
h
e
i
m
p
er
ce
p
tib
ilit
y
o
f
w
ater
m
ar
k
th
at
is
estab
li
s
h
ed
b
y
t
h
e
P
ea
k
S
ig
n
al
to
No
is
e
R
atio
(
P
SNR
)
.
I
t
m
ea
n
s
th
e
p
er
ce
p
tu
al
d
if
f
er
en
ce
li
n
k
in
g
th
e
w
a
ter
m
ar
k
ed
an
d
th
e
ac
t
u
al
r
ec
o
r
d
s
s
h
o
u
ld
b
e
i
n
s
ig
n
i
f
i
ca
n
t
to
th
e
h
u
m
a
n
e
y
e
[
9
]
.
F
u
r
th
er
m
o
r
e,
to
ac
h
ie
v
e
tr
a
n
s
p
ar
en
c
y
,
t
h
e
q
u
alit
y
o
f
t
h
e
w
ater
m
ar
k
a
n
d
ac
t
u
al
r
e
f
lectio
n
s
h
o
u
ld
n
o
t
b
e
af
f
ec
ted
b
y
th
e
w
ater
m
ar
k
i
n
g
p
r
o
ce
s
s
[
1
5
]
.
Dig
i
tal
w
a
ter
m
ar
k
i
n
g
i
s
ap
p
licab
le
i
n
t
h
e
s
p
atial
an
d
tr
a
n
s
f
o
r
m
s
p
h
er
es
f
o
r
t
h
e
ac
h
iev
e
m
e
n
t
o
f
r
o
b
u
s
t
n
es
s
a
n
d
i
m
p
er
ce
p
tib
il
it
y
.
I
n
s
p
atial
d
o
m
ai
n
p
r
o
ce
d
u
r
es,
th
e
w
ater
m
ar
k
is
e
m
b
ed
d
ed
s
tr
ai
g
h
t
to
th
e
p
ix
el
ar
ea
;
m
a
k
in
g
i
m
p
le
m
en
tatio
n
ea
s
ier
b
u
t
lac
k
s
r
o
b
u
s
t
n
ess
.
W
h
ile
i
n
tr
an
s
f
o
r
m
d
o
m
ain
p
r
o
ce
d
u
r
es
to
co
ef
f
icie
n
ts
t
h
en
f
ix
w
ate
r
m
ar
k
in
to
it.
T
h
en
,
to
o
b
tai
n
e
m
b
ed
d
ed
i
m
a
g
e
in
v
er
s
e
tr
an
s
f
o
r
m
is
ap
p
lied
.
I
t
p
o
s
s
ess
es
f
u
r
t
h
er
r
o
b
u
s
tn
es
s
,
f
e
w
er
co
m
m
a
n
d
o
f
en
d
less
q
u
alit
y
a
n
d
m
o
s
tl
y
is
ac
ce
p
tab
le
f
o
r
co
p
y
r
i
g
h
t
ap
p
licatio
n
.
T
h
e
m
o
s
t
r
eg
u
lar
l
y
u
tili
ze
d
m
et
h
o
d
s
ar
e
Dis
cr
ete
C
o
s
i
n
e
T
r
an
s
f
o
r
m
(
DC
T
)
d
o
m
ai
n
[
1
6
]
,
Dis
cr
ete
W
av
elet
T
r
an
s
f
o
r
m
(
DW
T
)
[
1
7
]
,
Sin
g
u
lar
Valu
e
Dec
o
m
p
o
s
itio
n
(
SVD)
[
1
8
]
an
d
L
if
tin
g
W
a
v
elet
T
r
an
s
f
o
r
m
(
L
W
T
)
[
1
9
,
2
0
]
.
T
r
an
s
f
o
r
m
i
n
g
d
o
m
ai
n
tec
h
n
iq
u
es
ar
e
cu
r
r
en
tl
y
m
o
r
e
ex
ten
s
i
v
e
d
u
e
to
n
o
w
co
m
e
i
n
to
m
o
r
e
w
id
el
y
u
s
ed
as
t
h
e
y
al
w
a
y
s
h
a
v
e
g
o
o
d
r
o
b
u
s
tn
es
s
to
co
m
m
o
n
i
m
ag
e
p
r
o
ce
s
s
i
n
g
.
W
h
ile
th
e
s
e
p
r
o
ce
d
u
r
es
en
tail
e
m
b
ed
d
in
g
th
e
w
ater
m
ar
k
i
n
t
h
e
h
o
s
t
‘
s
tr
an
s
f
o
r
m
d
o
m
ai
n
,
i
n
co
m
p
ar
is
o
n
to
s
p
atial,
th
eir
s
o
p
h
is
ticatio
n
,
r
o
b
u
s
tn
es
s
,
an
d
p
o
p
u
lar
ity
ar
e
h
ig
h
[
2
1
]
.
T
h
e
lif
ti
n
g
m
et
h
o
d
is
a
p
r
o
ce
d
u
r
e
f
o
r
estab
lis
h
i
n
g
b
o
th
th
e
w
a
v
elets
a
n
d
p
er
f
o
r
m
in
g
t
h
e
DW
T
.
T
h
er
e
is
v
alu
e
in
m
er
g
i
n
g
th
e
p
r
o
ce
d
u
r
e
an
d
d
esig
n
in
g
o
f
t
h
e
w
a
v
elet
f
ilter
s
w
h
ile
e
x
ec
u
t
i
n
g
t
h
e
w
a
v
elet
tr
an
s
f
o
r
m
,
h
er
ea
f
ter
r
ef
er
r
ed
to
as
th
e
s
ec
o
n
d
g
en
er
atio
n
w
av
ele
t
tr
an
s
f
o
r
m
.
T
h
e
p
r
o
ce
d
u
r
e
w
a
s
in
s
ti
tu
ted
b
y
W
i
m
S
w
eld
e
n
s
[
2
2
]
.
T
h
e
L
W
T
h
as
s
p
ec
ial
ad
v
a
n
t
ag
es
o
v
er
t
h
e
tr
ad
itio
n
al
f
ir
s
t
-
g
e
n
er
atio
n
w
a
v
elets
[
2
2
]
.
Fu
r
th
er
m
o
r
e,
th
e
SVD
is
s
u
itab
le
f
o
r
w
ater
m
ar
k
i
n
g
s
in
ce
s
li
g
h
t
ch
a
n
g
e
i
n
s
i
n
g
u
lar
v
al
u
e
d
o
es
n
'
t
in
f
l
u
e
n
ce
th
e
q
u
ali
t
y
o
f
th
e
i
m
a
g
e
[
1
8
]
.
Usi
n
g
L
W
T
co
m
b
in
ed
w
it
h
SV
D
lead
s
to
s
i
m
p
lif
icatio
n
o
f
w
ater
m
ar
k
r
ec
o
v
er
y
,
en
h
a
n
ce
s
t
h
e
r
o
b
u
s
tn
es
s
o
f
t
h
e
w
ater
m
ar
k
an
d
s
p
r
ea
d
s
th
e
w
ater
m
ar
k
th
r
o
u
g
h
o
u
t
th
e
s
p
ec
tr
u
m
[
1
9
]
.
Gen
er
all
y
,
th
e
w
ater
m
ar
k
ca
n
b
e
b
ala
n
ce
d
b
y
a
Scal
in
g
Fac
to
r
(
SF
)
u
ti
lize
d
to
m
an
a
g
e
t
h
e
s
tu
r
d
i
n
ess
o
f
th
e
w
ater
m
ar
k
.
Fo
r
s
o
m
e
SVD
-
b
ased
r
esear
ch
e
s
,
th
e
s
ca
li
n
g
f
ac
to
r
is
co
n
s
tan
t.
Ne
v
er
t
h
eles
s
,
ar
g
u
m
en
t
s
i
m
p
l
y
th
a
t
t
h
e
co
n
s
id
er
atio
n
o
f
a
s
o
le
an
d
s
tab
le
s
ca
li
n
g
f
ac
to
r
is
i
n
ap
p
licab
le
[
2
3
]
.
T
h
e
ex
ec
u
tio
n
o
f
th
e
w
ater
m
ar
k
i
n
g
ac
tiv
it
y
i
s
h
ig
h
l
y
d
ep
en
d
en
t
o
n
ad
o
p
tin
g
a
p
r
o
p
er
SF
.
A
h
i
g
h
er
SF
i
m
p
lie
s
h
ig
h
-
q
u
ali
t
y
d
i
s
to
r
tio
n
o
f
t
h
e
h
o
s
t
i
m
a
g
e
(
tr
an
s
p
ar
e
n
c
y
)
a
n
d
th
e
p
o
w
er
f
u
l
t
h
e
r
o
b
u
s
t
n
es
s
.
E
v
en
s
o
,
a
lo
w
er
SF
tr
an
s
lates
to
en
h
a
n
ce
d
i
m
ag
e
q
u
alit
y
an
d
t
h
e
w
ea
k
er
t
h
e
r
o
b
u
s
t
n
ess
[
2
4
]
.
T
h
e
in
co
r
p
o
r
ati
o
n
o
f
M
u
lt
ip
le
Scali
n
g
Facto
r
s
(
MSF)
r
at
h
er
t
h
an
a
Sin
g
le
Scalin
g
Facto
r
(
SS
F
)
h
as
h
i
g
h
er
ap
p
licab
ilit
y
f
o
r
m
o
d
i
f
y
i
n
g
all
th
e
p
ix
el
es
ti
m
ates
o
f
t
h
e
ac
tu
al
p
ictu
r
e
[
2
5
]
.
Fo
r
w
ater
m
ar
k
i
n
g
,
t
h
e
d
eter
m
in
atio
n
o
f
M
SF
s
e
s
ti
m
ates
i
s
a
d
if
f
ic
u
lt
p
r
o
b
lem
w
h
ich
i
s
o
p
tim
izatio
n
p
r
o
b
le
m
.
Mu
l
ti
-
Ob
j
ec
tiv
e
A
r
ti
f
icial
B
ee
C
o
l
o
n
y
(
MO
A
B
C
)
alg
o
r
ith
m
ca
n
b
e
u
s
ed
to
p
r
o
v
id
e
a
s
o
lu
tio
n
to
s
u
ch
a
p
r
o
b
le
m
.
T
h
e
alg
o
r
ith
m
r
ep
licate
s
th
e
i
n
tel
lig
e
n
t
f
o
r
ag
i
n
g
ch
ar
ac
ter
o
f
h
o
n
e
y
b
ee
s
w
ar
m
s
.
I
t
is
a
v
er
y
s
tr
aig
h
t
f
o
r
w
ar
d
,
r
o
b
u
s
t a
n
d
p
o
p
u
latio
n
-
b
ased
s
to
ch
asti
c
o
p
ti
m
izatio
n
alg
o
r
it
h
m
[
2
6
]
.
2.
L
I
T
E
R
AT
U
RE
R
E
VI
E
W
I
n
2
0
0
9
Kh
aled
L
o
u
k
h
ao
u
k
h
a
an
d
J
ea
n
-
Y
v
es
C
h
o
u
i
n
ar
d
[
2
7
]
,
s
u
g
g
e
s
ted
h
y
b
r
id
r
o
b
u
s
t
d
ig
ita
l
w
ater
m
ar
k
i
n
g
tec
h
n
iq
u
e
d
ep
e
n
d
in
g
o
n
SVD
an
d
L
W
T
.
I
n
th
i
s
al
g
o
r
ith
m
t
h
e
co
v
er
p
ict
u
r
e
is
tr
an
s
f
o
r
m
ed
u
s
i
n
g
2
-
le
v
el
L
W
T
,
a
s
u
b
-
b
an
d
is
s
elec
ted
,
an
d
in
v
er
s
e
lif
ti
n
g
i
s
p
er
f
o
r
m
ed
to
t
h
at
s
u
b
b
an
d
.
T
h
en
,
t
h
e
s
in
g
u
lar
esti
m
ate
o
f
w
ater
m
ar
k
i
m
a
g
e
is
e
m
b
ed
d
ed
to
s
in
g
u
l
ar
esti
m
ate
o
f
t
h
at
s
u
b
-
b
an
d
,
a
t
th
e
en
d
th
e
i
m
a
g
e
is
r
ec
o
n
s
tr
u
cted
.
T
h
e
p
r
o
p
o
s
e
d
m
eth
o
d
i
m
p
r
o
v
es
t
h
e
o
p
er
atio
n
o
f
t
h
e
w
ater
m
ar
k
i
n
g
al
g
o
r
ith
m
estab
li
s
h
ed
o
n
th
e
j
o
in
t
L
W
T
an
d
SVD
a
n
d
s
h
o
w
s
th
at
t
h
e
i
m
p
er
ce
p
tib
ilit
y
is
p
r
o
v
id
ed
a
s
w
el
l
as
g
r
ea
ter
r
o
b
u
s
tn
e
s
s
ag
a
in
s
t
co
m
m
o
n
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
.
I
n
2
0
1
1
Kh
aled
L
o
u
k
h
ao
u
k
h
a
et.
al.
[
2
5
]
,
p
r
esen
ted
a
r
o
b
u
s
t
w
ater
m
ar
k
in
g
alg
o
r
ith
m
estab
li
s
h
ed
o
n
L
W
T
an
d
SVD
u
s
in
g
MS
Fs
o
p
tim
ized
b
y
m
u
lt
i
-
o
b
j
ec
tiv
e
an
t
co
lo
n
y
o
p
ti
m
izat
io
n
(
MO
AC
O)
.
T
h
e
s
in
g
u
lar
es
ti
m
ates
o
f
th
e
b
in
ar
y
w
ater
m
a
r
k
ar
e
e
m
b
ed
d
ed
in
a
d
etail
s
u
b
-
b
a
n
d
o
f
h
o
s
t
p
ictu
r
e.
Fo
r
g
ain
in
g
th
e
to
p
p
r
o
b
ab
le
r
o
b
u
s
tn
es
s
m
i
n
u
s
d
r
o
p
p
in
g
w
ater
m
ar
k
tr
an
s
p
ar
e
n
c
y
,
MSF
is
u
tili
ze
d
a
s
an
alter
n
ati
v
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
21
,
No
.
2
,
Feb
r
u
ar
y
2
0
2
1
:
1
2
18
-
12
2
9
1220
w
ater
m
ar
k
i
n
g
s
ch
e
m
e
s
u
r
p
ass
es
S
SF
w
a
ter
m
ar
k
in
g
p
r
o
ce
d
u
r
es
in
r
elatio
n
to
i
m
p
er
ce
p
tib
ilit
y
a
n
d
r
o
b
u
s
t
n
e
s
s
.
A
l
s
o
,
th
e
p
r
o
b
le
m
o
f
in
co
r
r
ec
t
ce
r
tain
d
etec
tio
n
s
w
h
ic
h
i
n
f
lu
e
n
ce
s
m
o
s
t
SVD
-
w
ater
m
ar
k
in
g
al
g
o
r
ith
m
s
is
s
ettled
b
y
o
n
e
-
w
a
y
h
a
s
h
f
u
n
ct
io
n
s
a
n
d
w
ater
m
ar
k
e
n
cr
y
p
tio
n
.
I
n
2
0
1
2
Su
s
h
m
a
G.
Kej
g
ir
an
d
Ma
n
e
s
h
Ko
k
ar
e
[
9
]
,
p
r
o
p
o
s
ed
a
w
ater
m
ar
k
in
g
p
r
o
ce
d
u
r
e
b
ased
o
n
L
W
T
an
d
SVD.
I
n
t
h
is
m
et
h
o
d
,
th
e
o
r
ig
in
al
i
m
ag
e
i
s
tr
an
s
f
o
r
m
ed
u
s
i
n
g
L
W
T
in
to
s
u
b
-
b
an
d
s
.
I
n
te
n
s
ities
o
f
s
u
b
-
b
an
d
s
ar
e
co
m
p
ar
ed
to
th
e
co
m
p
u
ted
"
Q
-
v
alu
e"
,
th
e
s
u
b
-
b
an
d
p
o
s
s
es
s
i
n
g
en
er
g
y
h
i
g
h
er
i
n
co
m
p
ar
is
o
n
to
t
h
e
ca
lc
u
lated
"
Q
-
v
alu
e"
is
c
h
o
s
en
f
o
r
w
ater
m
ar
k
e
m
b
ed
d
in
g
.
SVD
m
a
tr
ix
is
o
b
tain
ed
f
o
r
th
i
s
s
u
b
-
b
an
d
a
n
d
u
ti
lized
to
e
m
b
ed
t
h
e
g
r
a
y
le
v
el
d
ig
ital
s
i
g
n
at
u
r
e
a
s
a
w
a
ter
m
ar
k
.
T
h
e
r
esu
l
ts
o
f
t
h
is
tec
h
n
iq
u
e
s
h
o
w
ad
v
an
ta
g
es
o
v
er
tech
n
iq
u
es
t
h
at
u
s
e
DW
T
in
s
tead
o
f
L
W
T
.
I
n
2
0
1
2
Yo
n
g
ch
a
n
g
C
h
e
n
a
n
d
et.
al.
[
2
1
]
,
p
r
o
p
o
s
ed
a
w
ate
r
m
ar
k
i
n
g
s
c
h
e
m
e
estab
li
s
h
ed
o
n
SVD
a
n
d
DW
T
w
it
h
a
n
ar
tific
ial
b
ee
co
lo
n
y
alg
o
r
ith
m
(
A
B
C
)
.
I
n
th
is
s
ch
e
m
e
t
h
e
s
i
m
ilar
it
y
m
ea
s
u
r
e
o
f
U
-
m
atr
i
x
f
o
r
o
w
n
er
s
h
ip
is
ch
ec
k
ed
to
s
o
lv
e
t
h
e
p
r
o
b
lem
o
f
f
alse
p
o
s
itio
n
d
etec
tio
n
.
T
o
o
b
tain
th
e
g
r
ea
test
f
ea
s
ib
le
r
o
b
u
s
tn
es
s
w
it
h
o
u
t d
r
o
p
p
in
g
t
h
e
tr
an
s
p
ar
e
n
c
y
,
a
n
ad
ap
tiv
e
s
ca
lin
g
f
ac
to
r
is
o
b
tain
ed
b
y
t
h
e
A
B
C
al
g
o
r
ith
m
.
2
.
1
.
Wa
v
elet
s
a
nd
lift
ing
s
che
m
e
W
av
elet
tr
an
s
f
o
r
m
(
W
T
)
is
o
n
e
o
f
th
e
m
o
s
t
p
o
p
u
lar
f
r
eq
u
e
n
c
y
d
o
m
ai
n
ex
a
m
p
les
[
2
2
,
2
3
]
.
W
av
elet
tr
an
s
f
o
n
n
h
a
s
b
ee
n
w
id
el
y
s
tu
d
ied
in
m
an
y
asp
ec
t
s
o
f
i
m
ag
e
p
r
o
ce
s
s
i
n
g
[
2
4
]
.
W
av
elets
ar
e
a
f
le
x
ib
le
in
s
tr
u
m
en
t
f
o
r
p
o
r
tr
a
y
in
g
co
m
m
o
n
f
u
n
c
tio
n
s
o
r
d
ata
s
ets.
T
h
e
y
ca
n
b
e
th
o
u
g
h
t
o
f
as
d
ata
e
s
tab
lis
h
in
g
b
lo
c
k
s
.
T
h
ey
h
a
v
e
a
n
es
s
en
t
ial
tr
ait
o
f
en
ab
li
n
g
ef
f
ec
t
iv
e
r
ep
r
ese
n
tatio
n
s
t
h
at
ca
n
b
e
ca
lc
u
late
d
w
it
h
s
p
ee
d
.
T
h
at
m
ea
n
s
t
h
e
y
h
a
v
e
t
h
e
ca
p
ab
ilit
y
to
q
u
ic
k
l
y
s
eiz
u
r
e
th
e
d
ata
s
et
ex
tr
ac
ts
u
s
in
g
m
i
n
i
m
al
co
ef
f
icie
n
ts
.
T
h
is
is
as
a
r
esu
lt
o
f
t
h
e
co
r
r
elatio
n
a
v
aila
b
le
in
m
a
n
y
d
ata
s
et
s
b
o
th
i
n
ti
m
e
a
n
d
f
r
eq
u
en
c
y
[
2
5
]
.
T
h
e
lif
ti
n
g
m
et
h
o
d
is
a
p
o
p
u
lar
p
r
o
ce
d
u
r
e
u
s
ed
in
b
io
r
th
o
g
o
n
al
w
a
v
elet
s
.
I
t
is
a
s
i
m
p
le
b
u
t
q
u
ite
p
o
w
er
f
u
l
to
o
l
f
o
r
th
e
co
n
s
tr
u
ctio
n
o
f
s
ec
o
n
d
-
g
e
n
er
atio
n
a
n
d
a
llo
w
s
f
o
r
t
h
e
e
f
f
icien
t
i
m
p
le
m
e
n
tat
io
n
o
f
in
teg
er
w
a
v
elet
tr
an
s
f
o
r
m
s
[
2
5
]
.
I
t
is
n
o
t
o
n
l
y
r
estric
ted
to
o
n
e
-
d
i
m
en
s
i
o
n
al
s
i
g
n
a
ls
;
it
ca
n
al
s
o
b
e
u
s
ed
f
o
r
t
w
o
-
d
i
m
e
n
s
io
n
al
s
i
g
n
al
s
[
2
8
]
.
T
h
e
lif
ti
n
g
p
r
o
ce
d
u
r
e
is
a
m
et
h
o
d
f
o
r
n
o
t
o
n
l
y
s
ch
e
m
i
n
g
w
a
v
elet
s
b
u
t
also
d
o
in
g
w
a
v
elet
tr
an
s
f
o
r
m
.
T
h
e
f
o
r
w
ar
d
li
f
ti
n
g
tech
n
iq
u
e
s
p
lits
t
h
e
p
r
o
v
id
ed
d
ata
s
et
b
ei
n
g
h
a
n
d
led
i
n
to
ev
en
h
al
f
a
n
d
o
d
d
h
al
f
[
9
]
.
I
t
is
i
m
p
o
r
ta
n
t
to
lin
k
th
e
p
h
ases
an
d
d
e
v
ice
th
e
w
a
v
elet
f
i
lter
s
d
u
r
in
g
w
av
ele
t
m
o
d
if
i
ca
tio
n
,
r
ef
er
r
ed
to
a
s
―seco
n
d
-
g
en
er
atio
n
w
a
v
ele
t
tr
an
s
f
o
r
m
‖.
T
h
e
d
is
cr
ete
w
av
ele
t
tr
an
s
f
o
r
m
u
s
e
s
m
a
n
y
f
i
lter
s
d
i
s
tin
c
tl
y
to
th
e
s
a
m
e
s
ig
n
al.
On
th
e
c
o
n
tr
ar
y
,
t
h
e
s
ig
n
al
is
s
p
lit
lik
e
a
zip
p
er
an
d
f
u
r
th
er
s
e
v
er
al
co
n
v
o
lu
tio
n
-
ac
cu
m
u
late
p
r
o
ce
s
s
e
s
ar
e
u
tili
ze
d
f
o
r
th
e
lif
ti
n
g
s
ch
e
m
e
[
2
9
]
.
T
h
e
lif
tin
g
s
ch
e
m
e
is
an
e
f
f
icie
n
t
i
m
p
le
m
en
ta
tio
n
o
f
a
w
a
v
elet
tr
an
s
f
o
r
m
a
l
g
o
r
ith
m
.
T
h
e
in
i
tial
d
ev
el
o
p
m
en
t
o
f
th
i
s
tec
h
n
iq
u
e
w
a
s
f
o
r
en
h
a
n
ce
m
e
n
t
o
f
t
h
e
w
a
v
elet
tr
an
s
f
o
r
m
b
u
t
later
e
x
p
an
s
io
n
w
as
m
ad
e
to
a
g
e
n
er
ic
tec
h
n
iq
u
e
to
es
ta
b
lis
h
t
h
e
s
o
-
ca
l
led
s
ec
o
n
d
-
g
e
n
er
atio
n
w
a
v
elet
s
(
t
h
at
ar
e
wav
elets
th
a
t
d
o
n
o
t
au
to
m
at
icall
y
u
tili
ze
s
i
m
i
lar
f
u
n
ctio
n
p
r
o
to
ty
p
e
at
v
ar
io
u
s
lev
els).
T
h
er
e
ar
e
g
r
ea
ter
f
lex
ib
ilit
y
a
n
d
m
u
ch
p
o
w
er
to
t
h
e
s
ec
o
n
d
-
g
e
n
er
atio
n
w
a
v
elet
s
i
n
co
m
p
ar
i
s
o
n
to
th
e
f
ir
s
t
-
g
e
n
er
atio
n
w
av
ele
ts
.
T
h
e
liftin
g
s
c
h
e
m
e
i
s
an
ap
p
licatio
n
o
f
th
e
f
ilter
i
n
g
p
r
o
ce
d
u
r
es
at
ev
er
y
p
h
ase
[
3
0
]
.
T
h
e
m
o
s
t
n
o
ticea
b
le
ad
v
an
ta
g
e
s
o
f
liftin
g
s
ch
e
m
es
ar
e
s
i
m
p
le
s
tr
u
ct
u
r
e,
r
ed
u
ctio
n
o
f
d
is
to
r
tio
n
a
n
d
a
lias
i
n
g
e
f
f
ec
ts
,
f
a
s
t
a
n
d
in
-
p
la
ce
co
m
p
u
tatio
n
o
f
w
a
v
elet
tr
an
s
f
o
r
m
,
th
at
is
t
h
er
e
is
n
o
n
ee
d
f
o
r
ad
d
itio
n
al
au
x
iliar
y
m
e
m
o
r
y
[
2
5
]
;
T
h
er
ef
o
r
e,
it
is
w
id
el
y
u
tili
ze
d
i
n
s
i
g
n
al
p
r
o
ce
s
s
in
g
.
A
cla
s
s
ic
li
f
t
in
g
p
h
a
s
e
en
tai
ls
th
r
ee
p
r
o
ce
d
u
r
es,
n
a
m
el
y
a
s
p
lit,
a
p
r
ed
ict,
an
d
an
u
p
d
ate
o
p
er
atio
n
.
Fo
r
w
ar
d
li
f
ti
n
g
a
n
d
in
v
er
s
e
li
f
ti
n
g
s
ta
g
es
ar
e
ex
h
ib
ited
i
n
Fi
g
u
r
e
1
an
d
Fi
g
u
r
e
2
,
s
ep
ar
atel
y
.
Fig
u
r
e
2
.
L
i
f
ti
n
g
s
c
h
e
m
e
f
o
r
w
ar
d
w
a
v
elet
tr
a
n
s
f
o
r
m
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
R
o
b
u
s
t wa
terma
r
kin
g
s
ch
eme
b
a
s
ed
LW
T a
n
d
S
V
D
u
s
in
g
a
r
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ificia
l b
ee
co
lo
n
y…
(
A
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a
n
M
o
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in
A
b
d
u
la
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)
1221
I
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ti
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v
elet
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g
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3
,
t
h
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i
g
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m
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lit
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b
an
d
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s
ep
ar
atel
y
)
[
2
9
]
.
T
h
en
t
h
e
p
r
ed
icate
s
tep
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ap
p
lied
to
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e
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u
r
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4
(
a)
.
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h
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o
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Fi
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Su
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m
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i
g
h
lev
els
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i
th
f
u
r
th
er
d
escr
ip
tio
n
b
y
t
h
e
s
m
all
-
s
ca
le
w
av
e
let
co
ef
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icien
ts
.
Fig
u
r
e
3
.
I
n
v
er
s
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li
f
ti
n
g
s
ch
e
m
e
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r
m
Fig
u
r
e
4
.
An
i
m
a
g
e
d
ec
o
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p
o
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itio
n
o
v
er
th
r
ee
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v
el
Gen
er
all
y
,
t
h
e
co
n
ce
n
tr
atio
n
o
f
m
u
ch
o
f
t
h
e
p
ictu
r
e
en
er
g
y
is
at
th
e
lo
w
-
f
r
eq
u
en
c
y
s
u
b
-
b
an
d
s
L
L
d
eg
r
ad
in
g
t
h
e
p
ictu
r
e
r
e
m
ar
k
ab
ly
.
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n
h
a
n
ce
m
en
t
o
f
r
o
b
u
s
t
n
es
s
is
p
o
s
s
ib
le
v
ia
h
id
i
n
g
in
th
e
lo
w
-
f
r
eq
u
en
c
y
s
u
b
-
b
an
d
s
[
1
5
]
.
Sev
er
al
w
av
e
let
-
d
o
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ai
n
w
ater
m
ar
k
i
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r
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ater
m
ar
k
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to
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id
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le
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f
r
eq
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en
c
y
s
u
b
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b
a
n
d
s
co
ef
f
icie
n
t
s
f
o
r
t
w
o
r
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alities
:
f
ir
s
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lo
w
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eq
u
en
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m
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ter
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h
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en
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e
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en
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;
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w
o
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h
i
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f
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en
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e
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ts
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e
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il
y
eli
m
i
n
ated
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ter
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w
p
ass
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ilter
in
g
[
3
1
]
.
3.
SI
N
G
U
L
AR
VA
L
U
E
DE
CO
M
P
O
SI
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m
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n
t
h
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is
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alize
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s
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h
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le
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y
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lize
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in
a
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e
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o
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s
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g
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alu
e
s
m
o
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ei
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a
m
o
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t
h
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m
o
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t
p
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er
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l
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i
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tec
h
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iq
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es
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lin
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r
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eb
r
a,
SVD
co
n
tain
s
s
tab
ilit
y
an
d
ef
f
ec
t
iv
e
n
es
s
f
o
r
s
p
litt
i
n
g
th
e
s
tr
u
ct
u
r
e
in
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llectio
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l
y
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d
ep
en
d
en
t
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n
s
tit
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en
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s
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ev
er
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e
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co
n
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n
g
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n
d
iv
id
u
al
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er
g
y
p
r
ese
n
tatio
n
[
3
2
]
,
it
p
ac
k
s
m
a
x
i
m
u
m
s
i
g
n
al
e
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er
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to
,
as
p
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i
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ef
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h
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s
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ta
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f
icie
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in
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u
m
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r
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ig
n
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s
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in
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tech
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iq
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ig
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en
h
a
n
ce
m
e
n
t,
an
d
i
m
a
g
e
f
ilter
in
g
.
I
n
w
ater
m
ar
k
in
g
,
S
VD
is
w
id
el
y
u
s
ed
b
ec
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e
o
f
t
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n
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g
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t
s
tates
to
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id
e
t
h
e
w
ater
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ar
k
e
f
f
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tiv
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w
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n
c
h
a
n
g
e
s
o
cc
u
r
in
lar
g
e
s
in
g
u
lar
v
alu
e
s
[
3
3
]
.
E
v
er
y
ac
tu
a
l
m
atr
ix
M
ca
n
b
e
d
ec
o
m
p
o
s
ed
b
y
S
VD
in
to
a
p
r
o
d
u
ct
o
f
3
m
atr
ic
es
[
2
1
]
as
s
h
o
w
n
i
n
Fig
u
r
e
5
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
21
,
No
.
2
,
Feb
r
u
ar
y
2
0
2
1
:
1
2
18
-
12
2
9
1222
Fig
u
r
e
5
.
I
llu
s
tr
atio
n
o
f
Dec
o
m
p
o
s
in
g
M
to
USVT
W
h
er
e
Ma
tr
ix
U
is
a
n
p
×
p
o
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r
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to
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tr
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t
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h
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m
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x
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ca
n
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3
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T
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s
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ar
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te
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lar
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m
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to
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ter
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ed
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is
r
ef
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to
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t
h
e
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ig
h
t
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lar
v
ec
to
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s
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E
v
er
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s
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n
g
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lar
v
al
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d
etails
t
h
e
l
u
m
i
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an
ce
(
b
r
ig
h
t
n
ess
)
o
f
a
p
ict
u
r
e
la
y
er
w
it
h
t
h
e
eq
u
iv
a
len
t
s
et
o
f
s
i
n
g
u
lar
v
e
cto
r
s
in
d
icati
n
g
t
h
e
g
eo
m
etr
y
o
f
t
h
e
p
ictu
r
e
la
y
er
[
2
1
]
.
Du
r
in
g
i
m
ag
e
tr
an
s
f
o
r
m
atio
n
u
s
i
n
g
SVD,
co
m
p
r
ess
io
n
d
o
es
n
o
t
tak
e
p
lace
,
r
ath
er
th
e
d
eta
ils
o
cc
u
p
y
a
f
o
r
m
w
h
er
e
t
h
e
i
n
itia
l
s
in
g
u
lar
v
al
u
e
h
as
a
h
i
g
h
er
q
u
a
n
tit
y
o
f
t
h
e
i
m
a
g
e
d
etail
s
.
T
h
is
e
n
tail
s
u
tili
za
t
io
n
o
f
m
i
n
i
m
al
s
in
g
u
lar
v
al
u
e
s
to
s
h
o
w
t
h
e
i
m
a
g
e
w
it
h
le
s
s
co
n
tr
ast
i
n
co
m
p
ar
is
o
n
to
t
h
e
ac
t
u
al
[
2
4
]
.
Ma
n
y
SV
D
ch
ar
ac
ter
is
tic
s
ar
e
v
er
y
s
i
g
n
if
i
ca
n
t
f
o
r
p
ictu
r
e
s
li
k
e;
its
g
r
ea
t
est
e
n
er
g
y
p
ac
k
in
g
,
r
eso
l
v
i
n
g
o
f
t
h
e
lea
s
t
-
s
q
u
ar
es
is
s
u
e,
ca
lcu
lat
in
g
p
s
e
u
d
o
-
in
v
e
r
s
e
o
f
a
m
atr
i
x
an
d
m
u
lt
iv
ar
iat
e
an
al
y
s
is
[
3
2
]
.
So
m
e
attr
ac
ted
atten
t
io
n
p
r
o
p
er
ties
th
at
i
n
f
l
u
en
ce
w
ater
m
ar
k
i
n
g
ar
e
m
en
t
io
n
ed
b
elo
w
:
a)
Fe
w
s
i
n
g
u
lar
v
a
lu
e
s
(
SVs
)
ca
n
co
n
s
tit
u
te
a
lar
g
e
s
ec
t
io
n
o
f
s
i
g
n
al
e
n
er
g
y
[
2
3
]
.
b)
T
h
e
SV'
s
o
f
an
i
m
ag
e
p
o
s
s
es
s
es
g
r
ea
t
s
tab
ilit
y
,
t
h
at
is
,
w
ith
litt
le
ad
d
itio
n
o
f
p
er
tu
r
b
atio
n
to
a
p
ictu
r
e,
th
er
e
is
n
o
s
ig
n
i
f
ica
n
t
alter
ati
o
n
to
its
Si
n
g
u
lar
v
al
u
e
s
[
3
4
]
.
I
n
o
th
er
w
o
r
d
s
,
litt
le
v
ar
iatio
n
s
o
f
s
in
g
u
lar
v
alu
e
s
h
a
v
e
n
o
n
o
tab
le
in
f
l
u
en
ce
o
n
th
e
q
u
alit
y
o
f
t
h
e
co
v
er
p
ictu
r
e.
c)
T
h
e
lar
g
est
o
f
th
e
m
o
d
if
ied
S
V's
ag
a
in
s
t
s
i
g
n
al
p
r
o
ce
s
s
i
n
g
attac
k
s
c
h
a
n
g
e
v
er
y
litt
le,
b
ec
au
s
e
o
f
p
er
f
ec
t
n
o
is
e
i
m
m
u
n
it
y
o
f
t
h
e
SV
's [
3
5
]
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
R
o
b
u
s
t wa
terma
r
kin
g
s
ch
eme
b
a
s
ed
LW
T a
n
d
S
V
D
u
s
in
g
a
r
t
ificia
l b
ee
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y…
(
A
d
n
a
n
M
o
h
s
in
A
b
d
u
la
z
ee
z
)
1223
3
.
1
.
Art
if
ici
a
l bee
co
lo
ny
(
A
B
C)
B
y
Der
v
i
s
Kar
ab
o
g
a
i
n
2
0
0
5
th
e
A
B
C
al
g
o
r
ith
m
is
a
m
o
n
g
t
h
e
m
a
n
y
cu
r
r
e
n
t
e
x
p
lain
ed
,
p
r
o
m
p
ted
b
y
th
e
cle
v
er
ch
ar
ac
ter
o
f
h
o
n
e
y
b
ee
s
[
3
6
]
.
I
t
is
ea
s
y
li
k
e
b
o
t
h
alg
o
r
it
h
m
s
P
ar
ticle
S
w
ar
m
Op
ti
m
izatio
n
(
P
SO)
an
d
Dif
f
er
en
tia
l
E
v
o
lu
tio
n
(
DE
)
an
d
u
tili
ze
s
u
s
u
al
co
n
tr
o
l
v
ar
iab
les
lik
e
t
h
e
s
ize
o
f
co
lo
n
y
an
d
m
a
x
i
m
u
m
n
u
m
b
er
o
f
c
y
cle
s
.
A
B
C
as
an
o
p
tim
iza
tio
n
i
n
s
tr
u
m
e
n
t
s
u
p
p
lies
a
p
o
p
u
latio
n
-
b
ased
s
ea
r
ch
tech
n
iq
u
e
w
h
er
e
in
d
iv
id
u
als
ter
m
ed
as
lo
ca
tio
n
s
ar
e
alter
ed
b
y
th
e
ar
ti
f
icial
b
ee
s
w
it
h
ti
m
e
an
d
th
e
b
ee
‘
s
p
r
o
j
ec
t
in
d
is
co
v
er
in
g
th
e
f
o
o
d
s
o
u
r
ce
ar
ea
s
w
it
h
m
o
r
e
n
ec
tar
am
o
u
n
t
a
n
d
last
l
y
t
h
e
o
n
e
w
ith
t
h
e
g
r
ea
te
s
t
n
ec
ta
r
[
3
7
-
4
5
]
Kar
ab
o
g
a
[
3
6
]
s
u
g
g
e
s
ted
th
e
A
B
C
al
g
o
r
ith
m
p
r
o
m
p
ted
b
y
t
h
is
f
o
r
ag
in
g
c
h
ar
ac
ter
o
f
h
o
n
e
y
b
ee
s
.
T
h
is
alg
o
r
it
h
m
co
n
s
id
er
s
a
n
ar
ea
t
h
at
p
r
o
v
id
e
s
f
o
o
d
co
n
s
id
er
ed
as
a
ca
n
d
id
ate
o
u
tco
m
e
f
o
r
t
h
e
p
r
o
b
le
m
o
f
o
p
ti
m
izat
io
n
a
n
d
th
e
o
u
tco
m
e
o
f
t
h
e
f
it
n
es
s
is
co
n
s
tit
u
ted
b
y
t
h
e
q
u
a
n
tit
y
o
f
n
ec
tar
in
t
h
e
f
o
o
d
o
r
ig
in
.
C
o
m
p
ar
ab
le
to
t
h
e
r
ea
l
b
ee
co
lo
n
y
is
th
e
ar
tific
ial
b
ee
s
co
m
p
r
is
i
n
g
o
f
e
m
p
lo
y
ed
b
ee
s
,
On
lo
o
k
er
s
an
d
s
co
u
t
s
.
I
n
AB
C
,
e
m
p
lo
y
ed
b
ee
s
co
v
er
h
al
f
o
f
t
h
e
p
o
p
u
latio
n
w
h
ile
th
e
o
th
er
h
al
f
ar
e
o
n
lo
o
k
er
s
.
T
h
e
a
s
s
u
m
p
tio
n
i
s
t
h
at
t
h
e
q
u
a
n
ti
t
y
o
f
f
o
o
d
o
r
ig
in
i
s
eq
u
al
to
th
e
n
u
m
b
er
o
f
e
m
p
lo
y
ed
b
ee
s
.
A
f
ter
ab
a
n
d
o
n
i
n
g
a
f
o
o
d
o
r
ig
in
,
t
h
e
e
m
p
lo
y
ed
b
ee
o
f
t
h
at
f
o
o
d
o
r
ig
in
b
ec
o
m
es a
s
co
u
t a
n
d
p
er
f
o
r
m
s
a
r
an
d
o
m
s
ea
r
ch
.
As
it's
d
escr
ib
ed
in
[
4
5
]
,
T
h
e
alg
o
r
ith
m
g
en
er
all
y
o
u
tp
er
f
o
r
m
ed
o
th
er
tech
n
iq
u
e
s
(
SIM
P
SA
,
NE
SIM
P
SA
,
G
A
,
A
NT
S)
th
at
w
er
e
co
m
p
ar
ed
w
it
h
it
i
n
r
elatio
n
to
h
o
w
f
as
t
o
p
ti
m
izatio
n
an
d
ac
cu
r
ac
y
t
h
e
r
esu
lt
s
ca
n
b
e
es
tab
lis
h
ed
.
T
h
e
A
B
C
a
lg
o
r
it
h
m
is
s
o
ea
s
y
i
n
co
m
p
ar
is
o
n
w
it
h
o
th
er
p
r
ev
ailin
g
s
w
ar
m
-
b
a
s
ed
alg
o
r
ith
m
s
.
He
n
ce
,
W
.
Z
o
u
a
n
d
et.
al.
[
2
6
]
d
ev
elo
p
ed
A
B
C
to
h
an
d
le
m
u
lt
i
-
o
b
j
ec
tiv
e
o
p
tim
izatio
n
is
s
u
e
s
.
I
n
th
is
al
g
o
r
ith
m
,
all
s
o
l
u
tio
n
s
ar
e
f
o
o
d
s
o
u
r
ce
ar
ea
s
li
k
e
all
b
ee
s
ar
e
co
n
s
id
er
ed
as
o
n
lo
o
k
er
b
ee
s
,
w
it
h
n
o
e
m
p
lo
y
ed
b
ee
s
an
d
s
co
u
t
s
.
I
n
MO
A
B
C
a
n
e
x
ter
n
al
ar
ch
i
v
e
i
s
u
tili
ze
d
to
s
to
r
e
p
ast
v
ec
to
r
s
f
o
u
n
d
alo
n
g
t
h
e
s
ea
r
c
h
p
r
o
ce
d
u
r
e.
I
n
ev
er
y
g
e
n
er
atio
n
,
ea
c
h
o
b
s
er
v
er
r
an
d
o
m
l
y
s
elec
ts
a
f
o
o
d
o
r
ig
in
f
r
o
m
a
n
o
u
ter
lo
g
,
p
r
o
ce
ed
s
to
t
h
e
f
o
o
d
o
r
ig
in
p
lace
,
an
d
s
elec
ts
a
cu
r
r
en
t
f
o
o
d
o
r
ig
in
.
I
n
th
e
in
it
ializati
o
n
p
h
ase
af
ter
p
r
o
d
u
cin
g
f
o
o
d
s
o
u
r
ce
p
o
s
itio
n
s
r
an
d
o
m
l
y
,
th
e
f
it
n
ess
o
f
th
e
s
e
p
o
s
itio
n
s
is
ev
al
u
ated
a
n
d
ar
e
s
to
r
ed
in
ex
ter
n
al
ar
c
h
i
v
e
E
A
.
I
n
t
h
e
o
n
lo
o
k
er
b
ee
s
'
p
h
a
s
e,
a
d
etailed
lear
n
in
g
p
r
o
ce
d
u
r
e
is
u
til
ized
f
o
r
th
e
p
r
o
d
u
ctio
n
o
f
n
e
w
s
o
l
u
tio
n
v
i.
E
v
er
y
b
ee
x
i
h
ap
h
az
ar
d
l
y
s
elec
t
s
m
d
i
m
e
n
s
io
n
s
a
n
d
d
is
co
v
er
s
f
r
o
m
an
i
n
f
u
s
io
n
t
h
at
i
s
h
ap
h
az
ar
d
l
y
c
h
o
s
en
f
r
o
m
E
A
.
T
h
e
p
r
o
d
u
ctio
n
o
f
th
e
cu
r
r
e
n
t in
f
u
s
io
n
is
b
y
u
tili
zi
n
g
th
e
s
u
cc
ee
d
i
n
g
e
x
p
r
ess
io
n
:
(
)
(
)
(
4
)
w
h
er
e
k
ϵ
(
1
,
2
,
.
.
.
.
p
)
is
in
d
ex
s
elec
tio
n
r
a
n
d
o
m
l
y
,
p
r
ep
r
esen
ts
th
e
s
o
lu
tio
n
s
n
u
m
b
er
in
t
h
e
E
A
.
in
d
icate
s
r
an
d
o
m
p
er
m
u
ta
tio
n
o
f
f
ir
s
t
i
n
teg
er
n
u
m
b
er
s
1
:
n
,
an
d
f
(
m
)
r
ep
r
esen
ts
w
h
ic
h
d
i
m
e
n
s
io
n
o
f
'
s
s
h
o
u
ld
lear
n
f
r
o
m
.
A
s
d
is
s
e
n
t
to
Φ
ij
in
o
r
i
g
in
a
l
A
B
C
tec
h
n
iq
u
e,
g
en
er
at
e
r
an
d
o
m
n
u
m
b
er
s
w
h
er
e
a
ll
n
u
m
b
er
s
ar
e
b
et
w
ee
n
[
0
,
2
]
.
T
h
is
m
o
d
if
icati
o
n
m
a
k
es t
h
e
p
o
ten
tial sear
c
h
s
p
ac
e
ar
o
u
n
d
E
Ak
.
Af
ter
g
e
n
er
ati
n
g
a
n
e
w
s
o
l
u
ti
o
n
,
th
e
f
it
n
ess
i
s
ca
lc
u
lated
t
h
en
t
h
e
m
ec
h
a
n
i
s
m
o
f
g
r
ee
d
y
ch
o
s
en
i
s
ap
p
lied
to
d
eter
m
in
e
w
h
ic
h
s
o
lu
tio
n
s
h
o
u
ld
en
ter
E
A
.
A
f
ter
ea
ch
g
en
er
at
io
n
,
w
h
er
e
th
e
all
o
ca
ted
s
ize
o
f
E
A
h
as
b
ee
n
e
x
ce
ed
ed
b
y
t
h
e
n
u
m
b
er
o
f
s
o
lu
tio
n
s
,
co
n
g
est
in
g
d
is
tan
ce
is
u
tili
ze
d
to
o
m
it
t
h
e
cr
o
w
d
ed
m
e
m
b
er
s
.
So
r
tin
g
p
o
p
u
latio
n
in
th
e
ex
t
er
n
al
ar
ch
i
v
e
f
r
o
m
t
h
e
f
u
n
cti
o
n
v
al
u
e
o
f
ea
c
h
o
b
j
ec
tiv
e
i
n
ascen
d
i
n
g
o
r
d
er
is
n
ee
d
ed
to
co
m
p
u
te
t
h
e
cr
o
w
d
i
n
g
d
is
tan
ce
.
Af
ter
th
at,
t
h
e
f
u
n
ctio
n
o
f
ea
c
h
o
b
j
ec
tiv
e,
s
o
lu
tio
n
s
o
f
th
e
b
o
u
n
d
ar
y
w
it
h
f
u
n
ct
io
n
v
al
u
e
s
(
s
m
allest
an
d
lar
g
est)
ar
e
e
m
p
lo
y
ed
as
in
f
i
n
ite
v
al
u
es
o
f
d
is
tan
ce
.
Ho
w
e
v
er
,
all
o
th
er
s
o
lu
tio
n
s
(
in
ter
m
ed
i
ate)
ar
e
e
m
p
lo
y
e
d
a
s
a
v
al
u
e
o
f
d
is
ta
n
ce
eq
u
al
to
th
e
a
b
s
o
lu
te
n
o
r
m
alize
d
v
ar
io
u
s
i
n
t
h
e
f
u
n
ctio
n
v
al
u
e
s
o
f
t
w
o
n
e
ig
h
b
o
r
in
g
s
o
lu
tio
n
s
.
T
h
e
p
r
o
ce
s
s
o
f
t
h
is
co
m
p
u
tatio
n
is
p
er
s
is
ten
t
w
it
h
f
u
n
c
tio
n
s
f
r
o
m
o
th
er
o
b
j
ec
tiv
es.
Ov
er
all,
t
h
e
v
al
u
e
o
f
cr
o
w
d
in
g
d
is
ta
n
ce
i
s
co
m
p
u
te
d
a
s
a
s
u
m
m
a
tio
n
o
f
in
d
iv
id
u
al
d
is
ta
n
ce
v
al
u
es
co
r
r
esp
o
n
d
in
g
to
th
e
v
al
u
es
o
f
e
ac
h
o
b
j
ec
tiv
e.
T
h
e
f
u
n
ctio
n
o
f
ea
ch
o
b
j
ec
tiv
e
is
n
o
r
m
alize
d
b
ef
o
r
e
co
m
p
u
ti
n
g
th
e
cr
o
w
d
i
n
g
d
i
s
tan
ce
[
3
1
,
46
].
4.
P
RO
P
O
SE
D
SCH
E
M
E
In
g
e
n
er
al,
r
ec
o
n
s
tr
u
ctio
n
o
f
i
m
ag
e
s
b
y
li
f
ti
n
g
w
a
v
elet
t
r
an
s
f
o
r
m
is
g
o
o
d
co
m
p
ar
ed
w
it
h
o
th
er
g
en
er
al
w
a
v
elet
tr
a
n
s
f
o
r
m
s
,
b
ec
au
s
e
it
co
n
f
ir
m
s
s
m
o
o
t
h
n
e
s
s
ad
r
ed
u
ce
aliasin
g
ef
f
ec
ts
.
U
s
in
g
L
W
T
in
cr
ea
s
es
th
e
r
o
b
u
s
t
n
es
s
o
f
e
m
b
ed
d
ed
w
ater
m
ar
k
i
n
co
v
er
i
m
ag
e,
r
ed
u
ce
s
lo
s
s
o
f
in
f
o
r
m
at
io
n
a
n
d
h
elp
s
to
r
ec
o
v
er
w
ater
m
ar
k
.
A
b
o
u
t
S
VD,
it
‘
s
s
tab
ilit
y
an
d
e
f
f
ec
ti
v
e
n
ess
en
ab
le
s
p
litt
i
n
g
th
e
s
y
s
te
m
in
to
a
p
air
o
f
li
n
ea
r
l
y
in
d
ep
en
d
en
t
e
le
m
e
n
t
s
.
So
,
w
at
er
m
ar
k
i
n
g
s
c
h
e
m
e
b
ased
o
n
S
VD
is
ad
v
an
ta
g
eo
u
s
s
i
n
ce
s
li
g
h
t
m
o
d
i
f
icatio
n
s
i
n
th
e
s
i
n
g
u
lar
v
al
u
es
lac
k
s
s
i
g
n
i
f
ica
n
t
ef
f
ec
t
o
n
th
e
q
u
alit
y
o
f
i
m
ag
e.
T
h
er
ef
o
r
e,
th
e
p
r
o
p
o
s
ed
s
ch
e
m
e
co
m
b
in
e
s
th
e
p
r
o
p
er
ties
o
f
b
o
th
L
W
T
an
d
SVD.
T
h
is
s
c
h
e
m
e
u
s
es
L
W
T
to
d
ec
o
m
p
o
s
e
th
e
o
b
j
ec
t
i
m
a
g
e
i
n
to
f
o
u
r
s
u
b
-
b
an
d
s
(
L
L
,
L
H,
H
L
,
HH)
.
Gen
er
all
y
,
m
o
s
t
o
f
t
h
e
e
n
er
g
y
o
f
i
m
a
g
e
i
s
f
o
c
u
s
ed
o
n
t
h
e
lo
w
er
f
r
eq
u
en
c
y
s
u
b
-
b
an
d
L
L
,
an
d
t
h
e
h
i
g
h
-
f
r
eq
u
en
c
y
s
u
b
-
b
a
n
d
HH
in
co
r
p
o
r
ates
th
e
ed
g
es
an
d
tex
t
u
r
es
o
f
th
e
i
m
a
g
e
w
h
er
e
ea
s
il
y
c
an
b
e
r
em
o
v
ed
b
y
lo
w
p
a
s
s
f
il
ter
.
Ho
w
ev
er
,
t
h
e
m
id
d
le
-
f
r
eq
u
e
n
c
y
s
u
b
-
b
an
d
L
H
a
n
d
H
L
ar
e
m
o
s
t
s
u
ita
b
le
f
o
r
e
m
b
ed
d
in
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
21
,
No
.
2
,
Feb
r
u
ar
y
2
0
2
1
:
1
2
18
-
12
2
9
1224
w
ater
m
ar
k
i
n
to
.
So
af
ter
d
ec
o
m
p
o
s
i
n
g
th
e
co
v
er
i
m
a
g
e
(
I
)
in
to
3
-
le
v
el
L
W
T
,
o
n
e
o
f
th
e
m
id
d
le
f
r
eq
u
e
n
c
y
s
u
b
-
b
an
d
s
(
L
H)
is
s
elec
ted
to
e
m
b
ed
th
e
w
a
ter
m
ar
k
in
to
it
b
y
ad
d
in
g
it
s
s
in
g
u
lar
v
al
u
e
w
it
h
s
i
n
g
u
lar
v
al
u
e
o
f
th
e
w
ater
m
ar
k
m
u
lti
p
lied
b
y
MSFs
,
as
s
h
o
w
n
i
n
f
lo
w
c
h
ar
t
1
.
Fu
r
th
er
m
o
r
e,
d
eter
m
i
n
i
n
g
th
e
MSF
s
v
al
u
es
is
co
m
p
le
x
p
r
o
b
le
m
w
h
ic
h
ca
n
b
e
s
h
o
w
n
as
o
p
ti
m
izatio
n
p
r
o
b
lem
w
h
ic
h
is
s
o
lv
ed
u
s
i
n
g
MO
A
B
C
O.
T
o
in
cr
ea
s
e
t
h
e
s
ec
u
r
i
t
y
o
f
t
h
e
p
r
o
p
o
s
ed
s
y
s
te
m
,
b
ef
o
r
e
t
h
e
h
id
in
g
p
r
o
ce
s
s
,
t
h
e
o
r
i
g
i
n
al
w
ate
r
m
ar
k
i
s
e
n
cr
y
p
ted
b
y
u
s
i
n
g
th
e
c
h
ao
tic
m
ap
,
as s
h
o
w
n
i
n
Fi
g
u
r
e
6
.
T
h
e
w
ater
m
ar
k
ex
tr
ac
tio
n
p
r
o
ce
d
u
r
e
is
a
n
i
n
v
er
s
e
o
f
t
h
e
e
m
b
ed
d
in
g
tec
h
n
iq
u
e.
B
ec
au
s
e
th
e
p
r
o
p
o
s
ed
w
ater
m
ar
k
s
c
h
e
m
e
i
s
a
n
o
t
-
b
lin
d
e
x
tr
ac
tio
n
s
tr
ateg
y
,
th
e
e
x
tr
ac
tio
n
p
r
o
ce
s
s
n
ee
d
s
in
f
o
r
m
a
tio
n
o
n
th
e
o
r
ig
i
n
al
i
m
a
g
e.
I
n
ad
d
itio
n
,
th
e
ex
tr
ac
ted
w
ater
m
ar
k
is
ch
ao
ticall
y
en
cr
y
p
ted
,
s
o
it
m
u
s
t
b
e
d
ec
r
y
p
ted
ch
ao
ticall
y
to
g
et
t
h
e
w
ater
m
a
r
k
i
m
a
g
e.
as s
h
o
w
n
i
n
Fi
g
u
r
e
7
.
Fig
u
r
e
6
.
Flo
w
c
h
ar
t o
f
e
m
b
ed
d
in
g
p
r
o
ce
s
s
T
h
e
p
r
o
p
o
s
ed
s
ch
e
m
e
u
s
es
MSF
i
n
s
tead
o
f
S
SF
to
i
m
p
r
o
v
e
v
i
s
u
al
q
u
alit
y
a
n
d
to
e
n
h
a
n
ce
t
h
e
r
o
b
u
s
tn
es
s
o
f
th
e
w
ater
m
ar
k
in
g
s
ch
e
m
e.
T
h
e
d
eter
m
in
at
io
n
o
f
th
e
o
p
ti
m
al
v
alu
e
s
f
o
r
MS
Fs
o
f
w
ater
m
ar
k
i
n
g
ca
n
b
e
v
ie
w
ed
as a
n
o
p
ti
m
izat
io
n
p
r
o
b
lem
,
t
h
er
ef
o
r
e
MO
A
B
C
o
p
ti
m
izatio
n
alg
o
r
it
h
m
is
u
s
ed
.
I
n
MO
A
B
C
t
h
er
e
ar
e
o
n
l
y
o
n
l
o
o
k
er
b
ee
s
,
th
e
alg
o
r
ith
m
s
tep
s
ar
e
illu
s
tr
ated
as f
o
llo
w
.
a)
Step
1
: I
n
itialize
th
e
f
o
o
d
s
o
u
r
ce
p
o
s
itio
n
s
x
i r
a
n
d
o
m
l
y
w
h
er
e
x
i
= { x
i1
,
x
i2
, .... , x
iD
}
an
d
i=1
,
2
,
.
.
.
.
NS.
W
h
er
e
NS is t
h
e
n
u
m
b
er
o
f
s
o
l
u
tio
n
s
.
b)
Step
2
: E
v
alu
ate
t
h
e
f
itn
e
s
s
o
f
in
itial
ized
s
o
lu
tio
n
s
.
c)
Step
3
: Sto
r
e
th
e
in
f
u
s
io
n
s
in
t
h
e
o
u
ts
id
e
ar
ch
iv
e
E
A
.
d)
Step
4
: Fo
r
ev
er
y
o
n
lo
o
k
er
b
ee
x
i.
Hap
h
az
ar
d
l
y
ch
o
o
s
e
a
s
o
lu
tio
n
k
f
r
o
m
E
A
,
w
h
er
e
k
≠
i.
C
r
ea
te
a
n
e
w
in
f
u
s
io
n
v
i
b
y
u
s
in
g
ex
p
r
es
s
io
n
(
4
)
C
alcu
la
te
th
e
f
it
n
es
s
o
f
t
h
e
n
e
w
s
o
l
u
tio
n
.
E
m
p
lo
y
a
g
r
ee
d
y
s
e
lectio
n
E
n
d
f
o
r
e)
Step
5
: E
v
alu
ate
t
h
e
f
itn
e
s
s
o
f
E
A
f)
Step
6
:
I
f
t
h
e
s
u
m
o
f
i
n
f
u
s
i
o
n
s
i
n
E
A
s
u
r
p
ass
N
S,
e
m
p
l
o
y
cr
o
w
d
i
n
g
d
is
ta
n
ce
to
d
is
m
is
s
cr
o
w
d
ed
p
o
p
u
lace
d
ep
en
d
in
g
o
n
f
it
n
ess
.
g)
Step
7
: Fi
n
d
th
e
b
est b
ee
in
E
A
,
t
h
e
o
n
e
h
a
v
i
n
g
s
m
allest
f
it
n
ess
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4752
R
o
b
u
s
t wa
terma
r
kin
g
s
ch
eme
b
a
s
ed
LW
T a
n
d
S
V
D
u
s
in
g
a
r
t
ificia
l b
ee
co
lo
n
y…
(
A
d
n
a
n
M
o
h
s
in
A
b
d
u
la
z
ee
z
)
1225
Fig
u
r
e
7
.
Flo
w
c
h
ar
t o
f
ex
tr
ac
ti
n
g
p
r
o
ce
s
s
T
o
m
ak
e
t
h
e
p
r
o
p
o
s
ed
s
ch
e
m
e
ac
h
ie
v
e
th
e
h
i
g
h
est
tr
a
n
s
p
ar
en
c
y
a
n
d
r
o
b
u
s
t
n
es
s
u
n
d
er
v
a
r
io
u
s
t
y
p
e
s
o
f
attac
k
s
,
t
h
e
ev
al
u
atio
n
o
f
f
i
tn
es
s
f
u
n
ct
io
n
s
h
o
u
ld
b
e
p
r
o
g
r
ess
ed
in
s
u
ch
a
w
a
y
to
p
r
esen
t
MSFs
w
h
ic
h
h
a
v
e
m
o
r
e
r
e
s
is
ta
n
ce
a
g
ain
s
t
attac
k
s
.
I
f
t
h
e
o
r
ig
i
n
al
co
v
er
i
m
a
g
e
h
as
b
ee
n
in
tr
o
d
u
ce
d
as
I
,
th
e
w
ater
m
ar
k
ed
i
m
a
g
e
as
I
w
a
n
d
th
e
w
ater
m
ar
k
a
s
W
,
th
en
t
h
e
ev
al
u
atio
n
o
f
t
h
e
f
it
n
ess
f
u
n
c
tio
n
o
f
M
SF
s
(
α
)
ca
n
b
e
il
lu
s
tr
ated
in
th
e
f
o
llo
w
i
n
g
in
s
tr
u
c
tio
n
:
1)
P
r
o
d
u
ce
th
e
w
a
ter
m
ar
k
ed
i
m
ag
e
I
w
b
y
e
m
b
ed
d
in
g
t
h
e
w
a
ter
m
ar
k
W
to
th
e
co
v
er
i
m
ag
e
I
,
u
s
in
g
t
h
e
e
m
b
ed
d
in
g
p
r
o
ce
s
s
.
2)
C
alcu
late
th
e
n
o
r
m
alize
d
co
r
r
elatio
n
b
et
w
ee
n
I
an
d
I
w
,
i.e
.
NC
(
I
,
I
w
)
3)
E
x
tr
ac
t
w
ater
m
ar
k
W
'
f
r
o
m
t
h
e
w
ater
m
ar
k
ed
i
m
ag
e
u
s
i
n
g
th
e
ex
tr
ac
tio
n
p
r
o
ce
s
s
.
4)
C
alcu
late
th
e
n
o
r
m
alize
d
co
r
r
elatio
n
b
et
w
ee
n
W
an
d
W
'
,
i.e
.
NC
(
W
,
W
'
)
5)
A
p
p
ly
T
w
a
t
e
r
m
a
r
k
at
t
a
ck
s
u
p
o
n
th
e
w
at
e
r
m
a
r
k
e
d
im
ag
e
I
w
to
c
r
e
a
t
e
T
a
t
t
a
ck
e
d
w
at
e
r
m
a
r
k
ed
im
ag
e
Î
w
.
6)
B
y
u
s
in
g
t
h
e
e
x
tr
ac
tio
n
p
r
o
ce
d
u
r
e,
s
ep
a
r
ate
th
e
w
ater
m
ar
k
s
Ŵ
i
f
r
o
m
t
h
e
attac
k
ed
w
ater
m
ar
k
ed
i
m
a
g
es
Î
w
.
W
h
er
e
i={
1
,
2
,
.
.
.
.
,
T
}.
7)
C
alcu
late
th
e
n
o
r
m
alize
d
co
r
r
elatio
n
b
et
w
ee
n
o
r
ig
i
n
al
w
ater
m
ar
k
W
an
d
th
e
s
et
o
f
ex
tr
ac
t
ed
w
ater
m
ar
k
s
f
r
o
m
attac
k
ed
w
a
ter
m
ar
k
ed
im
ag
e
s
.
8)
C
o
n
s
tr
u
ct
a
v
ec
to
r
o
f
f
it
n
es
s
v
alu
es,
d
ef
i
n
ed
as:
9)
E
v
alu
a
te
th
e
v
ec
to
r
o
f
f
it
n
ess
v
alu
e
s
ac
co
r
d
in
g
to
th
e
e
x
p
o
n
en
tiall
y
w
ei
g
h
ted
m
et
h
o
d
f
o
r
m
u
lti
-
o
b
j
ec
tiv
e
o
p
tim
izatio
n
:
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4752
I
n
d
o
n
esia
n
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
21
,
No
.
2
,
Feb
r
u
ar
y
2
0
2
1
:
1
2
18
-
12
2
9
1226
∑
(
)
(
(
)
)
(
5
)
W
h
er
e
w
,
p
,
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ig
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r
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ate
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ased
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CO
NCLU
SI
O
N
I
n
th
i
s
p
ap
er
,
w
e
p
r
o
p
o
s
ed
an
alg
o
r
it
h
m
f
o
r
w
ater
m
ar
k
e
m
b
ed
d
in
g
a
n
d
w
ater
m
ar
k
ex
tr
ac
tio
n
E
m
b
ed
d
in
g
e
n
cr
y
p
ted
w
a
ter
m
ar
k
to
h
ig
h
f
r
eq
u
en
c
y
s
u
b
b
an
d
s
allo
w
s
h
i
g
h
p
er
f
o
r
m
a
n
ce
w
a
ter
m
ar
k
e
x
tr
ac
tio
n
.
I
n
th
i
s
p
ap
er
a
s
em
i
-
b
li
n
d
w
ater
m
ar
k
i
n
g
alg
o
r
it
h
m
i
s
p
r
esen
ted
w
h
ic
h
is
es
tab
lis
h
e
d
o
n
lif
tin
g
w
a
v
elet
tr
an
s
f
o
r
m
an
d
s
i
n
g
u
lar
v
alu
e
d
ec
o
m
p
o
s
itio
n
.
Mu
ltip
le
s
ca
li
n
g
f
ac
to
r
s
ar
e
u
s
ed
in
s
tead
o
f
s
in
g
le
s
ca
li
n
g
f
ac
to
r
to
g
et
th
e
h
ig
h
e
s
t
p
r
o
b
ab
le
tr
an
s
p
ar
e
n
c
y
an
d
r
o
b
u
s
t
n
es
s
to
g
e
th
er
.
T
h
e
M
O
A
B
C
al
g
o
r
ith
m
is
u
s
ed
to
d
eter
m
in
e
p
o
ten
tial
MSF
s
.
Hi
g
h
tr
an
s
p
ar
en
c
y
is
o
b
tain
ed
s
i
n
ce
n
o
d
if
f
er
en
ce
ca
n
b
e
n
o
tic
ed
af
ter
e
m
b
ed
d
in
g
w
ater
m
ar
k
to
th
e
o
r
i
g
in
a
l
i
m
ag
e.
Go
o
d
r
o
b
u
s
tn
es
s
a
g
ain
s
t
v
ar
io
u
s
t
y
p
e
s
o
f
at
tack
s
is
n
o
ticed
.
I
n
ter
m
s
o
f
p
er
f
o
r
m
a
n
ce
a
n
d
P
SNR
.
B
y
in
cr
ea
s
in
g
th
e
le
v
el
s
o
f
d
ec
o
m
p
o
s
itio
n
f
o
r
th
e
w
ater
m
ar
k
ed
i
m
ag
e,
t
h
e
r
esi
s
tan
ce
ag
ain
s
t t
h
e
attac
k
s
an
d
t
h
e
q
u
a
lit
y
o
f
e
x
tr
ac
ted
w
ater
m
ar
k
ca
n
b
e
i
m
p
r
o
v
ed
.
RE
F
RE
NCE
[1
]
S
.
P
riy
a
,
B.
S
a
n
th
i
,
a
n
d
P
.
S
w
a
m
i
n
a
th
a
n
,
"
Im
a
g
e
w
a
ter
m
a
rk
in
g
tec
h
n
i
q
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e
s
-
a
re
v
iew
,
"
Res
e
a
rc
h
J
o
u
rn
a
l
o
f
Ap
p
li
e
d
S
c
ien
c
e
s,
En
g
in
e
e
rin
g
a
n
d
T
e
c
h
n
o
lo
g
y
,
v
o
l.
4
,
n
o
.
1
4
,
p
p
.
2
2
5
1
-
2
2
5
4
,
2
0
1
2
.
[2
]
Brif
c
a
n
i,
A
.
M
.
A
.
,
&
A
l
-
Ba
m
e
r
n
y
,
J.
N
.
"
Im
a
g
e
c
o
m
p
re
s
sio
n
a
n
a
l
y
sis
u
sin
g
m
u
lt
istag
e
v
e
c
to
r
q
u
a
n
ti
z
a
ti
o
n
b
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se
d
o
n
d
isc
re
te
w
a
v
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let
tran
s
f
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r
m
"
.
I
n
2
0
1
0
I
n
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
M
e
th
o
d
s
a
n
d
M
o
d
e
ls
in
Co
mp
u
ter
S
c
ien
c
e
(I
CM
2
CS
-
2
0
1
0
)
,
p
p
.
4
6
-
5
3
,
IEE
E
,
2
0
1
0
.
[3
]
P
ra
jw
a
las
i
m
h
a
,
S
.
N.,
C
h
e
th
a
n
S
u
p
u
t
h
ra
,
S
.
,
&
M
o
h
a
n
,
C.
S
.
"
P
e
rf
o
rm
a
n
c
e
a
n
a
l
y
sis o
f
DC
T
a
n
d
su
c
c
e
ss
iv
e
d
iv
isio
n
b
a
se
d
d
ig
it
a
l
im
a
g
e
w
a
ter
m
a
rk
in
g
sc
h
e
m
e
"
,
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
i
n
e
e
rin
g
a
n
d
Co
mp
u
ter
S
c
ien
c
e
(
IJ
EE
CS
)
,
v
o
l.
15
,
n
o
.
2
,
p
p
.
7
5
0
-
757
,
2
0
1
9
.
[4
]
A
b
d
u
lq
a
d
e
r,
D.
M
.
,
A
b
d
u
la
z
e
e
z
,
A
.
M
.
,
&
Zee
b
a
re
e
,
D.
Q.
"
M
a
c
h
in
e
L
e
a
rn
in
g
S
u
p
e
rv
ise
d
A
lg
o
rit
h
m
s
o
f
Ge
n
e
S
e
lec
ti
o
n
:
A
Re
v
ie
w
"
,
M
a
c
h
in
e
L
e
a
rn
in
g
,
v
o
l
.
62
,
n
o
.
3
,
2
0
2
0
.
[5
]
F
.
Ha
rtu
n
g
a
n
d
M
.
Ku
tt
e
r,
"
M
u
l
ti
m
e
d
ia
w
a
t
e
r
m
a
r
k
in
g
tec
h
n
iq
u
e
s
,
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Pro
c
e
e
d
in
g
s
o
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t
h
e
IEE
E
,
v
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l
.
8
7
,
n
o
.
7
,
p
p
.
1
0
7
9
-
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1
0
7
,
1
9
9
9
.
[6
]
I.
M
.
N.
A
d
e
e
n
,
A
.
M
.
A
b
d
u
laz
e
e
z
,
a
n
d
D.
Q.
Zee
b
a
re
e
,
"
S
y
st
e
m
a
t
ic
Re
v
ie
w
o
f
Un
su
p
e
rv
ise
d
G
e
n
o
m
ic
Clu
ste
rin
g
A
l
g
o
rit
h
m
s T
e
c
h
n
iq
u
e
s
f
o
r
Hig
h
Dim
e
n
sio
n
a
l
Da
tas
e
ts:
A
Re
v
i
e
w
"
,
M
a
c
h
in
e
L
e
a
r
n
in
g
,
v
o
l
.
62
,
n
o
.
3
,
2
0
2
0
.
[7
]
S
u
laim
a
n
,
D.
M
.
,
A
b
d
u
laz
e
e
z
,
A.
M
.
,
Ha
ro
n
,
H.,
&
S
a
d
i
q
,
S
.
S
.
"
Un
su
p
e
rv
ise
d
L
e
a
rn
in
g
A
p
p
ro
a
c
h
-
Ba
se
d
Ne
w
Op
ti
m
iza
ti
o
n
K
-
M
e
a
n
s
Clu
ste
rin
g
f
o
r
F
in
g
e
r
V
e
in
Im
a
g
e
L
o
c
a
li
z
a
ti
o
n
"
.
In
2
0
1
9
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Ad
v
a
n
c
e
d
S
c
ien
c
e
a
n
d
En
g
in
e
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ri
n
g
(
ICOAS
E)
,
p
p
.
8
2
-
87
.
I
EE
E
,
2
0
1
9
.
[8
]
Zee
b
a
re
e
,
D.
Q.,
Ha
ro
n
,
H.,
A
b
d
u
laz
e
e
z
,
A
.
M
.
,
&
Zeb
a
ri,
D.
A
.
"
T
r
a
in
a
b
le
M
o
d
e
l
Ba
se
d
o
n
Ne
w
Un
if
o
rm
L
BP
F
e
a
tu
re
to
I
d
e
n
ti
f
y
th
e
Risk
o
f
t
h
e
Bre
a
st
Ca
n
c
er
"
.
In
2
0
1
9
I
n
te
rn
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Ad
v
a
n
c
e
d
S
c
ien
c
e
a
n
d
En
g
i
n
e
e
rin
g
(
ICOAS
E)
,
p
p
.
1
0
6
-
1
1
1
.
IEE
E
,
2
0
1
9
.
[9
]
P
.
S
i
n
g
h
a
n
d
R
.
Ch
a
d
h
a
,
"
A
su
r
v
e
y
o
f
d
ig
it
a
l
wa
ter
m
a
r
k
in
g
tec
h
n
iq
u
e
s,
a
p
p
li
c
a
ti
o
n
s
a
n
d
a
tt
a
c
k
s,"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
E
n
g
i
n
e
e
rin
g
a
n
d
I
n
n
o
v
a
ti
v
e
T
e
c
h
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o
lo
g
y
(
IJ
EIT
)
,
v
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l.
2
,
n
o
.
9
,
p
p
.
1
6
5
-
1
7
5
,
2
0
1
3
.
[1
0
]
Al
-
Yo
u
su
f
,
F
.
Q.
A
.
,
&
Din
,
R.
"
Re
v
ie
w
o
n
se
c
u
re
d
d
a
ta
c
a
p
a
b
il
it
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o
f
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r
y
p
to
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ra
p
h
y
,
st
e
g
a
n
o
g
ra
p
h
y
,
a
n
d
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a
t
e
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m
a
r
k
in
g
d
o
m
a
in
"
,
In
d
o
n
e
si
a
n
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
E
n
g
i
n
e
e
rin
g
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
(
IJ
EE
C
S)
,
v
o
l.
17
,
n
o
.
2
,
p
p
.
1
0
5
3
-
1
0
5
9
,
2
0
2
0
.
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