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ar
k
e
d
im
a
g
e.
W
h
ile
t
h
e
w
ater
m
ar
k
ca
n
ea
s
il
y
b
e
r
e
m
o
v
ed
w
h
e
n
th
e
w
ater
m
ar
k
ed
im
ag
e
w
as
co
m
p
r
es
s
ed
b
y
J
P
E
G.
L
u
m
i
n
a
n
ce
an
d
ch
r
o
m
i
n
an
ce
b
l
u
e
e
x
ih
ib
ite
l
ess
s
e
n
s
iti
v
it
y
to
h
u
m
an
e
y
e
s
.
T
h
er
ef
o
r
e,
w
ater
m
ar
k
b
its
ar
e
e
m
b
ed
d
ed
in
to
lu
m
in
a
n
ce
an
d
c
h
r
o
m
i
n
an
ce
b
lu
e
co
m
p
o
n
e
n
t
s
.
E
m
b
ed
d
in
g
o
f
m
u
ltip
le
w
ater
m
ar
k
s
is
p
er
f
o
r
m
ed
b
y
ex
a
m
in
i
n
g
th
e
r
elatio
n
s
h
ip
o
f
U
3,
1
an
d
U
4,
1
co
ef
f
icie
n
ts
o
f
SVD.
T
o
en
h
an
ce
th
e
s
ec
u
r
it
y
o
f
w
ater
m
ar
k
ed
i
m
a
g
es,
t
h
e
t
w
o
w
a
ter
m
ar
k
s
ar
e
s
cr
a
m
b
led
b
y
A
r
n
o
ld
ch
a
o
tic.
Fin
all
y
,
t
h
e
s
e
lecte
d
b
lo
ck
s
ar
e
i
n
v
er
s
ed
b
y
SVD
a
n
d
DC
T
to
g
et
t
h
e
w
a
te
r
m
ar
k
ed
i
m
ag
e.
T
h
e
p
r
o
p
o
s
ed
s
ch
e
m
e
ca
n
ac
h
ie
v
e
an
i
m
p
r
o
v
ed
r
o
b
u
s
t
n
ess
an
d
i
m
p
er
ce
p
tib
ilit
y
o
f
w
ater
m
ar
k
ed
im
a
g
e.
T
h
e
r
elate
d
w
o
r
k
s
d
e
m
o
n
s
tr
at
e
th
at
m
u
ltip
le
w
ater
m
ar
k
s
ar
e
a
v
ital
r
o
le
i
n
m
u
lti
m
ed
ia
s
ec
u
r
it
y
.
T
h
i
s
w
ater
m
ar
k
i
n
g
m
o
d
el
ca
n
b
e
i
m
p
r
o
v
ed
b
y
t
h
e
h
y
b
r
id
tech
n
iq
u
es
a
n
d
ex
tr
a
s
ec
u
r
it
y
ca
n
b
e
ac
h
iev
ed
u
s
i
n
g
s
cr
a
m
b
led
w
ater
m
ar
k
s
.
A
n
e
w
h
y
b
r
id
b
lo
ck
-
b
ased
i
m
ag
e
w
ater
m
ar
k
in
g
i
s
p
r
o
p
o
s
ed
b
ased
o
n
th
e
H
V
S
ch
ar
ac
ter
is
tic
s
an
d
th
e
e
m
b
e
d
d
in
g
p
r
o
ce
s
s
is
ca
r
r
ied
o
u
t
b
ased
o
n
m
o
d
i
f
y
i
n
g
f
ir
s
t
co
lu
m
n
o
f
o
r
th
o
g
o
n
a
l
m
atr
i
x
U
o
f
SVD.
T
h
is
s
ch
e
m
e
attain
s
h
i
g
h
r
o
b
u
s
tn
e
s
s
ag
ain
s
t
attac
k
s
.
T
h
e
h
ig
h
li
g
h
t
s
an
d
s
o
m
e
s
p
ec
ial
f
ea
t
u
r
es o
f
t
h
e
p
r
o
p
o
s
ed
s
ch
em
e
ar
e
p
r
o
v
id
ed
as f
o
llo
w
s
:
a.
Ou
r
s
ch
e
m
e
p
r
o
p
o
s
es
m
u
ltip
l
e
w
ater
m
ar
k
s
e
m
b
ed
d
in
g
w
h
i
ch
co
n
s
id
er
s
e
n
tr
o
p
y
a
n
d
ed
g
e
en
tr
o
p
y
.
T
h
is
p
ap
er
p
r
o
p
o
s
es
an
o
p
ti
m
a
l
th
r
esh
o
ld
f
o
r
m
u
lt
ip
le
w
ater
m
ar
k
in
g
i
n
l
u
m
in
a
n
ce
a
n
d
ch
r
o
m
i
n
an
ce
b
l
u
e.
Ou
r
s
ch
e
m
e
p
r
o
d
u
ce
s
m
i
n
i
m
u
m
d
i
s
to
r
tio
n
in
t
h
e
v
is
u
al
w
ater
m
ar
k
ed
i
m
a
g
e.
b.
Mu
ltip
le
w
ater
m
ar
k
s
e
m
b
ed
d
i
n
g
ar
e
p
er
f
o
r
m
ed
b
y
e
x
a
m
i
n
i
n
g
t
h
e
f
ir
s
t
co
lu
m
n
o
f
U
m
a
t
r
ix
.
W
ater
m
ar
k
e
m
b
ed
d
in
g
o
n
U
m
atr
ix
o
f
l
u
m
i
n
an
ce
a
n
d
ch
r
o
m
i
n
an
ce
b
lu
e
ca
n
i
m
p
r
o
v
e
th
e
r
o
b
u
s
t
n
es
s
an
d
in
v
is
ib
ilit
y
o
f
m
u
ltip
le
w
ater
m
ar
k
s
.
c.
C
o
n
f
id
en
tia
ll
y
o
f
w
ater
m
ar
k
i
m
a
g
e
i
s
a
n
i
m
p
o
r
tan
t
i
n
f
o
r
m
atio
n
,
it
s
h
o
u
ld
b
e
e
x
tr
ac
te
d
b
y
au
th
o
r
ized
u
s
er
s
.
T
o
i
m
p
r
o
v
e
th
e
s
ec
u
r
it
y
lev
e
l,
m
u
ltip
le
w
a
ter
m
ar
k
s
a
r
e
s
cr
a
m
b
led
b
ef
o
r
e
th
e
y
ar
e
e
m
b
ed
d
ed
in
to
lu
m
in
a
n
ce
a
n
d
ch
r
o
m
i
n
a
n
ce
b
lu
e
w
h
ich
ca
n
p
r
o
v
id
e
ex
tr
a
s
e
cu
r
it
y
i
n
t
h
e
w
ater
m
ar
k
ed
i
m
a
g
e.
d.
B
y
f
i
n
d
in
g
o
p
ti
m
al
t
h
r
es
h
o
ld
s
f
o
r
ea
ch
i
m
a
g
e
co
m
p
o
n
e
n
t,
t
h
e
q
u
alit
y
o
f
t
h
e
w
ater
m
ar
k
ed
i
m
ag
e
p
r
o
d
u
ce
s
h
ig
h
i
m
a
g
e
q
u
alit
y
an
d
t
h
e
r
ec
o
v
er
ed
w
ater
m
ar
k
r
esis
tan
t
s
a
g
ain
s
t d
if
f
er
e
n
t t
y
p
e
s
o
f
attac
k
.
2.
RE
S
E
ARCH
M
E
T
H
O
D
2
.
1
.
Arno
ld
s
cr
a
m
b
lin
g
W
ater
m
ar
k
i
m
a
g
es
ar
e
s
cr
am
b
led
b
y
A
r
n
o
ld
ch
ao
tic
m
ap
to
in
cr
ea
s
e
th
e
s
ec
u
r
it
y
o
f
m
u
ltip
le
w
ater
m
ar
k
i
n
g
.
Scr
a
m
b
led
w
a
t
er
m
ar
k
s
ca
n
n
o
t
b
e
r
ec
o
v
er
ed
w
it
h
o
u
t
a
s
ec
r
et
k
e
y
ev
e
n
att
ac
k
er
s
s
u
cc
es
s
f
u
l
l
y
ex
tr
ac
t
t
h
e
w
ater
m
ar
k
f
r
o
m
lu
m
i
n
an
ce
an
d
c
h
r
o
m
i
n
a
n
ce
b
l
u
e
co
m
p
o
n
e
n
ts
o
f
th
e
w
ater
m
ar
k
ed
i
m
ag
e.
A
r
n
o
ld
s
cr
a
m
b
li
n
g
tr
a
n
s
f
o
r
m
atio
n
is
d
ef
i
n
ed
b
y
[
1
9
]
:
N
y
x
y
x
m
o
d
2
1
1
1
'
'
(
1
)
w
h
er
e
'
'
y
x
r
ep
r
esen
ts
v
ec
to
r
p
o
s
itio
n
af
ter
s
h
i
f
ti
n
g
,
y
x
r
ep
r
esen
ts
o
r
ig
in
a
l
v
ec
to
r
p
o
s
itio
n
b
ef
o
r
e
s
h
i
f
ti
n
g
an
d
mo
d
d
en
o
tes
th
e
m
o
d
u
lu
s
o
p
er
atio
n
af
ter
d
iv
is
io
n
w
it
h
N
.
T
h
e
p
ar
am
eter
N
r
ep
r
esen
ts
t
h
e
p
er
io
d
o
f
A
r
n
o
ld
s
cr
a
m
b
li
n
g.
I
n
t
h
i
s
ex
p
er
im
e
n
t,
t
h
e
n
u
m
b
er
o
f
iter
at
io
n
o
r
d
er
N
is
u
s
ed
a
s
a
s
ec
r
et
k
e
y
f
o
r
s
cr
a
m
b
li
n
g
tr
an
s
f
o
r
m
atio
n
.
I
n
o
r
d
er
to
in
v
er
s
e
th
e
w
ater
m
ar
k
i
m
a
g
e,
t
h
e
in
v
er
s
e
A
r
n
o
ld
tr
an
s
f
o
r
m
a
tio
n
ca
n
b
e
d
ef
i
n
ed
b
y
:
N
y
x
y
x
m
o
d
'
'
1
1
1
2
(
2
)
2
.
2
.
H
u
m
a
n v
is
ua
l
cha
ra
ct
er
is
t
ic
s
Hu
m
an
v
i
s
u
al
c
h
ar
ac
ter
is
tic
s
less
s
e
n
s
itiv
e
a
g
ai
n
s
t
r
ed
u
n
d
an
c
y
o
f
i
m
a
g
e
i
n
f
o
r
m
atio
n
.
I
t
ca
n
b
e
d
escr
ib
ed
th
r
o
u
g
h
e
n
tr
o
p
y
to
d
eter
m
in
e
m
o
s
t
r
ed
u
n
d
an
t
i
m
ag
e
i
n
f
o
r
m
atio
n
.
E
n
tr
o
p
y
w
a
s
ex
p
lo
ited
to
s
elec
t
s
ig
n
i
f
ica
n
t e
m
b
ed
d
in
g
r
eg
io
n
.
E
n
tr
o
p
y
a
r
e
ap
p
lied
to
d
eter
m
i
n
e
e
m
b
ed
d
in
g
lo
ca
tio
n
s
f
o
r
m
u
ltip
le
w
ater
m
ar
k
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
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8
8
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8708
I
n
t J
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lec
&
C
o
m
p
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g
,
Vo
l.
8
,
No
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4
,
A
u
g
u
s
t
2018
:
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5
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–
2
5
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7
2580
i
m
a
g
e.
E
m
b
ed
d
in
g
ce
r
tain
a
m
o
u
n
t
o
f
w
ater
m
ar
k
b
its
i
n
th
e
lu
m
in
a
n
ce
a
n
d
ch
r
o
m
i
n
a
n
ce
m
u
s
t
b
e
in
v
i
s
ib
le
to
h
u
m
a
n
e
y
e
s
.
T
h
e
en
tr
o
p
y
w
a
s
u
s
ed
to
m
ea
s
u
r
e
th
e
s
p
atia
l
co
r
r
elatio
n
o
f
n
ei
g
h
b
o
r
p
ix
e
ls
.
E
n
tr
o
p
y
o
f
an
N
-
s
tate
is
d
ef
in
ed
b
y
[
2
0
]
:
2
1
l
o
g
(
)
N
ii
i
E
p
p
(
3
)
I
m
ag
e
ed
g
e
i
s
an
i
m
p
o
r
ta
n
t
in
f
o
r
m
atio
n
o
f
i
m
a
g
e
c
h
ar
ac
ter
is
tics
.
E
d
g
e
en
tr
o
p
y
o
f
a
n
i
m
a
g
e
b
lo
ck
i
s
co
n
s
id
er
ed
f
o
r
e
m
b
ed
d
in
g
r
eg
i
o
n
s
.
E
d
g
e
en
tr
o
p
y
i
s
g
i
v
e
n
as
f
o
llo
w
s
:
1
1
e
x
p
i
N
p
e
d
g
e
i
i
Ep
(
4
)
w
h
er
e
i
p
d
en
o
tes
th
e
o
cc
u
r
r
en
ce
p
r
o
b
ab
ilit
y
o
f
i
-
th
p
ix
el
w
it
h
01
i
p
an
d
1
-
i
p
r
ep
r
esen
t
s
t
h
e
u
n
ce
r
tai
n
t
y
o
r
ig
n
o
r
an
ce
o
f
t
h
e
p
ix
el
v
al
u
e
.
T
h
e
v
alu
es
o
b
tain
ed
f
r
o
m
c
o
m
b
i
n
atio
n
b
et
w
ee
n
e
n
tr
o
p
y
a
n
d
ed
g
e
en
tr
o
p
y
ar
e
s
o
r
ted
in
ascen
d
i
n
g
o
r
d
er
an
d
th
e
lo
w
est
v
al
u
e
ar
e
ch
o
o
s
en
a
s
e
m
b
ed
d
in
g
r
eg
io
n
s
.
2
.
3
.
DCT
A
tr
u
e
-
co
lo
r
h
o
s
t
i
m
a
g
e
i
s
tr
an
s
f
o
r
m
ed
i
n
to
Y
C
b
C
r
co
lo
r
s
p
ac
e.
E
ac
h
co
m
p
o
n
e
n
t
(
l
u
m
i
n
an
ce
an
d
ch
r
o
m
i
n
an
ce
b
lu
e)
is
d
iv
id
ed
in
to
s
m
a
ll
b
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o
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h
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t
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o
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in
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t i
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m
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y
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2
1
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:
11
00
(
2
1
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2
1
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c
o
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o
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mn
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o
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h
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t
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icien
t
s
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e
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e
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tr
an
s
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th
e
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u
b
-
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t
io
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2
.
4
.
SVD
T
h
e
SVD
f
ac
to
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izes
a
r
ea
l
o
r
co
m
p
le
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atr
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ee
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ich
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d
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tr
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f
A
ca
n
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e
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ted
as f
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w
s
[
2
2
]
:
T
A
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V
(
8
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i
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ir
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h
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t
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ltip
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ar
k
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e
D
C
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-
SVD
d
o
m
ain
.
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h
e
r
u
les
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e
d
escr
ib
e
d
in
th
e
p
r
o
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ed
w
ater
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ar
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e
m
b
ed
d
in
g
an
d
ex
tr
ac
tio
n
al
g
o
r
ith
m
s
i
n
t
h
e
n
e
x
t sectio
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J
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lec
&
C
o
m
p
E
n
g
I
SS
N:
2
0
8
8
-
8708
A
B
lin
d
Mu
ltip
le
W
a
terma
r
k
s
b
a
s
ed
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n
Hu
ma
n
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a
l Ch
a
r
a
cteris
tic
s
(
F
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a
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r
n
a
w
a
n
)
2581
2
.
5
.
I
m
perc
e
ptibility
m
ea
s
ure
m
e
nt
T
h
is
s
ec
tio
n
d
escr
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es
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e
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etr
ics
to
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alu
ate
th
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p
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o
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ed
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ter
m
ar
k
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s
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o
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tr
ate
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er
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th
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h
e
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ater
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ated
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tr
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ct
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r
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SS
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M)
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SS
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M
is
co
m
p
u
ted
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y
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(
,
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(
,
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(
,
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(
,
)
S
S
I
M
x
y
l
x
y
c
x
y
s
x
y
(
9)
w
h
er
e
α
>0
,
β
>0
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γ
>0
,
ar
e
p
a
r
a
m
eter
s
w
h
ic
h
ca
n
b
e
ad
j
u
s
ted
to
s
ig
n
if
y
t
h
eir
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elativ
e
i
m
p
o
r
tan
ce
.
2
.
6
.
R
o
bu
s
t
ne
s
s
m
ea
s
ure
m
ent
R
o
b
u
s
t
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ater
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ar
k
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t
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ea
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u
r
ed
b
y
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r
m
alize
d
C
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o
s
s
-
C
o
r
r
elatio
n
(
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d
B
it
E
r
r
o
r
R
ate
(
B
E
R
)
.
NC
an
d
B
E
R
ar
e
g
iv
e
n
as
[
2
3
]
-
[
2
5
]
:
11
22
1
1
1
1
(
,
)
.
(
,
)
(
,
)
(
,
)
MN
ij
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N
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N
i
j
i
j
W
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j
W
i
j
NC
W
i
j
W
i
j
(
1
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11
(
,
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(
,
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MN
ij
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i
j
W
i
j
BER
MN
(
11)
w
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d
en
o
tes
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s
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p
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n
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d
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r
ep
r
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t
r
o
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s
a
n
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co
lu
m
n
s
s
ize
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f
t
h
e
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ater
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ar
k
i
m
a
g
e,
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,
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j
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th
e
e
x
tr
ac
ted
w
ater
m
ar
k
a
n
d
th
e
W
(
i
,
j
)
is
t
h
e
o
r
ig
in
al
w
ater
m
ar
k
.
3.
P
RO
P
O
SE
D
SCH
E
M
E
3
.
1
.
Wa
t
er
m
a
r
k
i
ns
er
t
io
n
W
ater
m
ar
k
i
n
s
er
tio
n
p
r
o
ce
s
s
i
s
d
iv
id
ed
i
n
to
ten
s
tep
s
.
T
h
e
p
r
o
p
o
s
ed
m
u
ltip
le
w
ater
m
ar
k
s
s
ch
e
m
e
i
s
d
escr
ib
ed
in
A
l
g
o
r
ith
m
1
.
A
l
g
o
r
ith
m
1
: W
ater
m
ar
k
I
n
s
er
tio
n
I
n
p
u
t
:
H
o
st
i
mag
e
;
w
a
t
e
r
mark
;
t
h
r
e
sh
o
l
d
(
T
)
S
t
e
p
1
:
T
h
e
c
o
v
e
r
c
o
l
o
r
i
mag
e
i
s
c
o
n
v
e
r
t
e
d
t
o
Y
C
b
C
r
c
o
l
o
r
c
h
a
n
n
e
l
s.
Em
b
e
d
d
i
n
g
m
u
l
t
i
p
l
e
w
a
t
e
r
mark
s
i
s
p
e
r
f
o
r
m
e
d
i
n
L
u
mi
n
a
n
c
e
(
Y
)
a
n
d
C
h
r
o
m
i
n
a
n
c
e
-
B
l
u
e
(
C
b
)
.
S
t
e
p
2
:
L
u
mi
n
a
n
c
e
a
n
d
c
h
r
o
mi
n
a
n
c
e
b
l
u
e
a
r
e
d
i
v
i
d
e
d
b
y
8
×
8
p
i
x
e
l
s.
S
t
e
p
3
:
C
a
l
c
u
l
a
t
e
e
n
t
r
o
p
y
v
a
l
u
e
s fo
r
e
a
c
h
b
l
o
c
k
.
S
t
e
p
4
:
S
e
l
e
c
t
b
l
o
c
k
s
b
a
se
d
o
n
e
n
t
r
o
p
y
v
a
l
u
e
s
a
n
d
s
a
v
e
t
h
e
x
a
n
d
y
c
o
o
r
d
i
n
a
t
e
s
S
t
e
p
5
:
B
o
t
h
b
i
n
a
r
y
w
a
t
e
r
mark
s a
r
e
scramb
l
e
d
b
y
A
r
n
o
l
d
c
h
a
o
t
i
c
.
S
t
e
p
6
:
A
p
p
l
y
D
C
T
f
o
r
e
a
c
h
se
l
e
c
t
e
d
b
l
o
c
k
s.
S
t
e
p
7
:
P
e
r
f
o
r
m SV
D
b
a
se
d
o
n
b
l
o
c
k
-
b
a
se
d
D
C
T
c
o
e
f
f
i
c
i
e
n
t
s fo
r
w
a
t
e
r
mark
e
mb
e
d
d
i
n
g
.
S
t
e
p
8
:
F
o
r
e
a
c
h
w
a
t
e
r
mark
b
i
t
,
e
m
b
e
d
w
a
t
e
r
mark
a
c
c
o
r
d
i
n
g
t
o
t
h
e
r
u
l
e
s a
s
f
o
l
l
o
w
s
:
R
u
l
e
1
:
i
f
t
h
e
n
u
mb
e
r
o
f
b
i
t
s
a
r
e
l
e
ss
t
h
a
n
max
i
mu
m
w
a
t
e
r
mark
b
i
t
s,
c
a
l
c
u
l
a
t
e
t
h
e
a
v
e
r
a
g
e
U
3,
1
a
n
d
U
4,
1
c
o
e
f
f
i
c
i
e
n
t
s
a
n
d
s
a
v
e
i
t
t
o
m
.
R
u
l
e
2
:
i
f
t
h
e
b
i
n
a
r
y
w
a
t
e
r
mark
e
q
u
a
l
t
o
1
a
n
d
U
3
,
1
c
o
e
f
f
i
c
i
e
n
t
i
s
l
e
ss
t
h
a
n
U
4,
1
c
o
e
f
f
i
c
i
e
n
t
,
mo
d
i
f
y
t
h
e
c
o
e
f
f
i
c
i
e
n
t
s
b
y
:
U
3
,1
=
m
+
T
/
2
;
U
4
,
1
=
m
-
T
/
2
.
R
u
l
e
3
:
i
f
t
h
e
b
i
n
a
r
y
w
a
t
e
r
mark
b
i
t
e
q
u
a
l
t
o
0
a
n
d
U
3,
1
c
o
e
f
f
i
c
i
e
n
t
i
s
l
e
ss
t
h
a
n
U
4,
1
c
o
e
f
f
i
c
i
e
n
t
,
mo
d
i
f
y
t
h
e
c
o
e
f
f
i
c
i
e
n
t
s
b
y
:
U
3,
1
=
m
-
T
/
2
;
U
4,
1
=
m
+
T
/
2
.
S
t
e
p
9
:
P
e
r
f
o
r
m t
h
e
i
n
v
e
r
se
S
V
D
,
t
h
e
n
a
p
p
l
y
i
n
g
t
h
e
i
n
v
e
r
se
D
C
T
o
n
e
a
c
h
se
l
e
c
t
e
d
b
l
o
c
k
.
S
t
e
p
1
0
:
M
e
r
g
i
n
g
a
l
l
Y
C
b
C
r
c
o
mp
o
n
e
n
t
s
a
n
d
c
o
n
v
e
r
t
Y
C
b
C
r
t
o
R
G
B
c
o
l
o
r
i
mag
e
t
o
o
b
t
a
i
n
t
h
e
w
a
t
e
r
mark
e
d
i
mag
e
.
O
u
t
p
u
t
:
W
a
t
e
r
mark
e
d
i
mag
e
c
o
n
t
a
i
n
i
n
g
a
w
a
t
e
r
mark
3
.
2
.
Wa
t
er
m
a
r
k
e
x
t
ra
ct
io
n
Step
-
by
-
s
tep
s
to
ex
tr
ac
t
m
u
ltip
le
w
a
ter
m
ar
k
s
ar
e
d
iv
id
ed
in
to
s
ev
e
n
t
s
tep
s
as
d
e
s
cr
ib
ed
in
A
l
g
o
r
ith
m
2
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8708
I
n
t J
E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
8
,
No
.
4
,
A
u
g
u
s
t
2018
:
2
5
7
8
–
2
5
8
7
2582
A
l
g
o
r
ith
m
2
: W
ater
m
ar
k
E
x
tr
ac
tio
n
I
n
p
u
t
:
W
a
t
e
r
mark
e
d
i
m
a
g
e
S
t
e
p
1
:
A
w
a
t
e
r
mark
e
d
c
o
l
o
r
i
mag
e
i
s
c
o
n
v
e
r
t
e
d
t
o
Y
C
b
C
r
c
o
l
o
r
c
h
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1
,
2
0
1
7
.
[5
]
H.
-
T
.
Hu
a
n
d
L
.
-
Y.
Hs
u
,
“
Ex
p
lo
rin
g
DWT
-
S
V
D
-
DCT
f
e
a
tu
re
p
a
ra
m
e
ters
f
o
r
ro
b
u
st
m
u
lt
ip
le
w
a
ter
m
a
rk
in
g
a
g
a
in
st
JP
EG
a
n
d
J
P
EG
2
0
0
0
c
o
m
p
re
ss
io
n
,
”
Co
m
p
u
ter
s a
n
d
El
e
c
trica
l
E
n
g
in
e
e
rin
g
,
v
o
l.
4
1
,
p
p
.
0
5
2
-
0
6
3
,
2
0
1
5
.
[6
]
C.
-
C.
L
a
i,
“
A
n
i
m
p
ro
v
e
d
S
VD
-
b
a
se
d
w
a
ter
m
a
rk
in
g
s
c
h
e
m
e
u
sin
g
h
u
m
a
n
v
isu
a
l
c
h
a
ra
c
te
risti
c
s,”
Op
ti
c
s
Co
mm
u
n
ica
ti
o
n
s,
v
o
l
.
2
8
4
,
n
o
.
4
,
p
p
.
9
3
8
-
9
4
4
,
2
0
1
1
[7
]
M
.
L
i
a
n
d
C.
Ha
n
,
“
A
DC
T
-
S
V
D d
o
m
a
in
wa
ter
m
a
r
k
in
g
f
o
r
c
o
lo
r
d
i
g
it
a
l
i
m
a
g
e
b
a
se
d
o
n
c
o
m
p
re
ss
e
d
se
n
sin
g
th
e
o
ry
a
n
d
c
h
a
o
s
t
h
e
o
ry
,
”
S
e
v
e
n
th
In
ter
n
a
ti
o
n
a
l
S
y
mp
o
siu
m
o
n
C
o
mp
u
ta
ti
o
n
a
l
In
telli
g
e
n
c
e
a
n
d
De
sig
n
(
IS
CID)
,
p
p
.
3
5
-
3
8
,
2
0
1
4
.
[8
]
M
.
A
li
,
C.
W
.
A
h
n
,
M
.
P
a
n
t
,
“
A r
o
b
u
st i
m
a
g
e
wa
ter
m
a
rk
in
g
te
c
h
n
iq
u
e
u
sin
g
S
V
D an
d
d
if
f
e
re
n
ti
a
l
e
v
o
lu
ti
o
n
in
DCT
d
o
m
a
in
,
”
Op
ti
k
,
v
o
l.
1
2
5
,
p
p
.
4
2
8
-
4
3
4
,
2
0
1
4
.
[9
]
C.
C.
Ch
a
n
g
,
P
.
T
sa
i,
C.
C.
L
in
,
“
S
V
D
-
b
a
se
d
d
ig
it
a
l
im
a
g
e
w
a
te
rm
a
rk
in
g
sc
h
e
m
e
,
”
Pa
tt
e
rn
Rec
o
g
n
it
io
n
L
e
tt
e
r,
v
o
l.
2
6
,
n
o
.
1
0
,
p
p
.
1
5
7
7
–
1
5
8
6
,
2
0
0
5
.
[1
0
]
K.L
.
Ch
u
n
g
,
W
.
N.
Ya
n
g
,
Y.H.
Hu
a
n
g
,
S
.
T
.
W
u
,
Y.C.
Hs
u
,
“
On
S
V
D
-
b
a
se
d
w
a
ter
m
a
rk
in
g
a
lg
o
rit
h
m
,
”
Ap
p
li
e
d
M
a
th
e
ma
ti
c
s a
n
d
Co
mp
u
ta
ti
o
n
,
v
o
l.
1
8
8
,
n
o
.
1
,
p
p
.
5
4
-
5
7
,
2
0
0
7
.
[1
1
]
M
.
Q.
F
a
n
,
H.X.
W
a
n
g
,
S
.
K.
L
i,
“
Re
stu
d
y
o
n
S
V
D
-
b
a
se
d
w
a
ter
m
a
rk
in
g
s
c
h
e
m
e
,
”
Ap
p
li
e
d
M
a
th
e
ma
t
ics
a
n
d
Co
mp
u
t
a
ti
o
n
,
v
o
l.
2
0
3
,
n
o
.
3
p
p
.
9
2
6
-
9
3
0
,
2
0
0
8
.
[1
2
]
V
.
K
h
a
n
d
u
ja,
S
.
Ch
a
k
ra
v
e
rt
y
a
n
d
O.
P
.
V
e
rm
a
,
“
En
a
b
li
n
g
in
f
o
rm
a
ti
o
n
re
c
o
v
e
ry
w
it
h
o
w
n
e
rsh
i
p
u
si
n
g
ro
b
u
s
t
m
u
lt
ip
le w
a
ter
m
a
rk
s,”
J
o
u
rn
a
l
o
f
In
fo
rm
a
t
io
n
S
e
c
u
rity
a
n
d
A
p
p
l
ica
ti
o
n
s
,
v
o
l.
2
9
,
p
p
.
8
0
-
9
2
,
2
0
1
6
.
[1
3
]
V
.
K
h
a
n
d
u
ja,
S
.
Ch
a
k
ra
v
e
rt
y
a
n
d
O.
P
.
V
e
rm
a
,
R.
T
a
n
d
o
n
,
S
.
G
o
e
l,
“
A
ro
b
u
st
m
u
lt
ip
le
w
a
ter
m
a
r
k
in
g
tec
h
n
iq
u
e
f
o
r
in
f
o
rm
a
ti
o
n
re
c
o
v
e
r
y
,
”
IEE
E
In
ter
n
a
ti
o
n
a
l
Co
n
fer
e
n
c
e
o
n
Ad
v
a
n
c
e
Co
mp
u
ti
n
g
,
p
p
.
2
5
0
-
2
5
5
,
2
0
1
4
.
[1
4
]
S
.
Be
h
n
ia,
M
.
T
e
sh
n
e
h
lab
,
P
.
Ay
u
b
i,
“
M
u
lt
i
p
le
-
w
a
ter
m
a
r
k
in
g
sc
h
e
m
e
b
a
se
d
o
n
im
p
ro
v
e
d
c
h
a
o
ti
c
m
a
p
s,”
Co
mm
u
n
ica
ti
o
n
s i
n
No
n
li
n
e
a
r S
c
i
e
n
c
e
a
n
d
Nu
me
ric
a
l
S
imu
l
a
ti
o
n
,
v
o
l.
1
5
,
n
o
.
9
,
p
p
.
2
4
6
9
-
2
4
7
8
,
2
0
1
0
.
[1
5
]
H.
-
C.
Hu
a
n
g
,
S
.
-
C.
Ch
u
,
J.
-
S
.
P
a
n
,
C.
-
Y.
H
u
a
n
g
a
n
d
B.
-
Y.
L
iao
,
“
T
a
b
u
se
a
rc
h
b
a
se
d
m
u
lt
i
-
wa
ter
m
a
rk
s
e
m
b
e
d
d
in
g
a
lg
o
rit
h
m
w
it
h
m
u
lt
ip
le d
e
sc
rip
ti
o
n
c
o
d
i
n
g
,
”
In
fo
rm
a
ti
o
n
S
c
ien
c
e
s
,
v
o
l.
1
8
1
,
n
o
.
1
6
,
p
p
.
3
3
7
9
-
3
3
9
6
,
2
0
1
1
.
[1
6
]
N.
M
o
h
a
n
a
n
th
in
i
a
n
d
G
.
Ya
m
u
n
a
,
“
Co
m
p
a
riso
n
o
f
m
u
lt
ip
le
w
a
te
rm
a
rk
in
g
tec
h
n
iq
u
e
s
u
sin
g
g
e
n
e
ti
c
a
lg
o
rit
h
m
s,”
J
o
u
rn
a
l
o
f
El
e
c
trica
l
S
y
ste
ms
a
n
d
In
fo
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
3
,
n
o
.
1
,
p
p
.
6
8
-
8
0
,
2
0
1
6
.
[1
7
]
R.
Ch
a
m
la
w
i,
A
,
Kh
a
n
a
n
d
I.
Us
m
a
n
,
“
A
u
th
e
n
ti
c
a
ti
o
n
a
n
d
re
c
o
v
e
r
y
o
f
i
m
a
g
e
s
u
sin
g
m
u
lt
ip
le
wa
ter
m
a
r
k
s,”
Co
mp
u
ter
s &
El
e
c
trica
l
En
g
in
e
e
r
in
g
,
v
o
l.
3
6
,
n
o
.
3
,
p
p
.
5
7
8
-
5
8
4
,
2
0
1
0
.
[1
8
]
R.
C.
G
o
n
z
a
lez
,
R.
E.
W
o
o
d
,
“
Dig
it
a
l
im
a
g
e
p
ro
c
e
ss
in
g
,
2
n
d
e
d
it
i
o
n
,
”
In
d
i
a
:
Pea
rs
o
n
E
d
u
c
a
ti
o
n
,
2
0
0
2
.
[1
9
]
M
.
Kh
a
li
li
,
“
DCT
-
A
rn
o
ld
c
h
a
o
ti
c
b
a
se
d
w
a
ter
m
a
rk
in
g
u
sin
g
JP
EG
-
YCb
Cr,
”
Op
ti
k
-
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
fo
r L
ig
h
t
a
n
d
El
e
c
tro
n
Op
ti
c
s
,
v
o
l.
1
2
6
,
n
o
.
3
,
p
p
.
4
3
6
7
-
4
3
7
1
,
2
0
1
5
.
[2
0
]
F
.
Er
n
a
w
a
n
,
M
.
Ra
m
a
li
n
g
a
m
,
A
.
S
.
S
a
d
iq
,
Z.
M
u
sta
ff
a
,
“
A
n
im
p
ro
v
e
d
im
p
e
rc
e
p
ti
b
il
it
y
a
n
d
ro
b
u
st
n
e
ss
o
f
4
x
4
DCT
-
S
V
D
im
a
g
e
w
a
ter
m
a
rk
in
g
u
sin
g
m
o
d
if
ied
e
n
tro
p
y
,
”
J
o
u
rn
a
l
o
f
T
e
lec
o
mm
u
n
ica
ti
o
n
,
El
e
c
tro
n
ic
a
n
d
Co
m
p
u
ter
En
g
i
n
e
e
rin
g
,
v
o
l.
9
,
n
o
.
2
-
7
,
p
p
.
1
1
1
-
1
1
6
,
2
0
1
7
.
[2
1
]
F
.
Ern
a
w
a
n
a
n
d
S
.
H.
Nu
g
ra
in
i
,
“
T
h
e
o
p
ti
m
a
l
q
u
a
n
ti
z
a
ti
o
n
m
a
tri
c
e
s f
o
r
JP
EG
i
m
a
g
e
c
o
m
p
re
ss
io
n
f
r
o
m
p
s
y
c
h
o
v
isu
a
l
th
re
sh
o
l
d
,
”
J
o
u
rn
a
l
o
f
T
h
e
o
re
ti
c
a
l
a
n
d
A
p
p
l
ied
I
n
fo
rm
a
ti
o
n
T
e
c
h
n
o
lo
g
y
,
v
o
l.
7
0
,
n
o
.
3
,
p
p
.
5
6
6
-
5
7
2
,
2
0
1
4
.
[2
2
]
S.
-
L
.
Jia
,
“
A
n
o
v
e
l
b
li
n
d
c
o
l
o
r
i
m
a
g
e
s
w
a
t
e
r
m
a
r
k
in
g
b
a
se
d
o
n
S
V
D,”
Op
ti
k
-
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
fo
r
L
ig
h
t
a
n
d
El
e
c
tro
n
Op
t
ics
,
v
o
l.
1
2
5
,
n
o
.
1
2
,
p
p
.
2
8
6
8
-
2
8
7
4
,
2
0
1
4
.
[2
3
]
M
.
Bo
u
ss
if
,
N.
A
lo
u
i,
A
.
Ch
e
ri
f
,
“
Ne
w
W
a
ter
m
a
rk
in
g
/E
n
c
r
y
p
ti
o
n
M
e
th
o
d
f
o
r
M
e
d
ica
l
I
m
a
g
e
s F
u
ll
P
r
o
tec
ti
o
n
in
m
-
He
a
lt
h
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
,
v
o
l.
7
,
n
o
.
6
,
p
p
.
3
3
8
5
-
3
3
9
4
,
2
0
1
7
.
[2
4
]
V
.
A
.
Ku
m
a
r,
C.
Dh
a
r
m
a
ra
j,
Ch
.
S
.
Ra
o
,
“
A
H
y
b
rid
Dig
it
a
l
W
a
te
rm
a
rk
in
g
A
p
p
ro
a
c
h
Us
in
g
W
a
v
e
lets
a
n
d
L
S
B,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
E
lec
trica
l
a
n
d
C
o
mp
u
ter
En
g
in
e
e
rin
g
,
v
o
l.
7
,
n
o
.
5
,
p
p
.
2
4
8
3
-
2
4
9
5
,
2
0
1
7
.
[2
5
]
I.
Iw
u
t,
G
.
Bu
d
im
a
n
,
L
.
No
v
a
m
i
z
a
n
ti
,
“
Op
ti
m
iza
ti
o
n
o
f
Disc
re
t
e
C
o
sin
e
T
ra
n
sf
o
r
m
-
Ba
se
d
I
m
a
g
e
Wat
e
r
m
a
r
k
in
g
b
y
G
e
n
e
ti
c
s
A
l
g
o
rit
h
m
,
”
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
El
e
c
trica
l
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
,
v
o
l.
4
,
n
o
.
1
,
p
p
.
9
1
-
1
0
3
,
2
0
1
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