I
nd
o
ne
s
ia
n J
o
urna
l o
f
E
lect
rica
l En
g
ineering
a
nd
Co
m
pu
t
er
Science
Vo
l.
24
,
No
.
2
,
N
o
v
em
b
e
r
2
0
2
1
,
p
p
.
86
4
~
8
70
I
SS
N:
2
5
0
2
-
4
7
5
2
,
DOI
: 1
0
.
1
1
5
9
1
/ijeecs.v
24
.i
2
.
pp
86
4
-
8
70
864
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
ee
cs.ia
esco
r
e.
co
m
Self
em
bedding
di
g
ital wa
termark
using
hybrid me
t
ho
d ag
a
inst
co
mpres
sio
n atta
ck
Na
s
r
E
dd
ine
T
o
ua
t
i
,
Abde
l
m
o
un
a
im
M
o
ula
y
L
a
k
hd
a
r
In
fo
rm
a
ti
o
n
P
r
o
c
e
ss
in
g
a
n
d
Tele
c
o
m
m
u
n
ica
ti
o
n
Lab
o
ra
to
r
y
(LT
I
T)
,
F
a
c
u
lt
y
o
f
Tec
h
n
o
lo
g
y
,
Un
iv
e
rsity
TAHRI M
o
h
a
m
m
e
d
Be
c
h
a
r,
Be
c
h
a
r,
Alg
e
ria
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Au
g
22
,
2
0
2
1
R
ev
is
ed
Sep
22
,
2
0
2
1
Acc
ep
ted
Sep
27
,
2
0
2
1
In
th
e
m
o
d
e
rn
ti
m
e
in
tera
c
ti
n
g
with
d
ig
it
a
l
wo
rl
d
b
e
c
o
m
e
sta
n
d
a
rd
li
fe
a
c
ti
v
it
y
,
h
u
m
a
n
n
e
e
d
a
wa
y
to
p
r
o
tec
t
p
ro
p
e
rti
e
s
a
s
in
d
iv
i
d
u
a
ls
o
r
c
o
rp
o
ra
ls,
a
n
d
we
d
o
t
h
a
t
b
y
e
m
b
e
d
d
i
n
g
a
d
ig
it
a
l
m
a
rk
t
o
t
h
e
tar
g
e
t,
a
n
d
th
is
tec
h
n
iq
u
e
c
a
ll
d
ig
it
a
l
wa
term
a
rk
in
g
.
B
u
t
th
e
re
stil
l
is
a
c
h
a
n
c
e
to
m
a
n
ip
u
lat
e
o
r
e
v
e
n
re
m
o
v
e
th
is
m
a
rk
s
we
e
m
b
e
d
f
o
r
p
r
o
tec
ti
o
n
wit
h
v
a
rio
u
s
a
tt
a
c
k
s
l
ik
e
a
d
d
in
g
n
o
ise
s,
c
o
m
p
re
ss
io
n
-
d
e
c
o
m
p
re
ss
io
n
o
r
b
it
s
m
a
n
ip
u
latio
n
s,
a
n
d
th
a
t
wh
y
c
o
m
p
a
n
io
n
s,
i
n
d
i
v
i
d
u
a
ls,
la
b
o
ra
t
o
ries
a
re
stil
l
d
e
v
e
lo
p
in
g
n
e
w
m
e
th
o
d
s
t
o
e
m
b
e
d
th
is
m
a
rk
s
a
n
d
m
a
k
e
t
h
e
m
m
o
re
ro
b
u
st
a
n
d
m
o
re
h
a
rd
to
d
e
tec
t
fo
r
o
th
e
rs.
Th
e
re
a
re
s
o
m
a
n
y
m
e
th
o
d
s
fo
r
d
ig
i
tal
wa
term
a
rk
in
g
,
s
o
w
e
c
h
o
se
t
h
e
lea
st
sig
n
ifi
c
a
n
t
b
it
s
wa
term
a
rk
in
g
(LS
B
-
wa
term
a
rk
in
g
)
t
o
p
ro
v
i
d
e
a
n
in
v
isi
b
le
d
i
g
it
a
l
wa
term
a
rk
in
g
,
a
n
d
o
n
t
o
p
o
f
th
a
t
we
p
r
o
c
e
e
d
with
th
e
b
l
in
d
LS
B
-
wa
term
a
rk
in
g
m
e
th
o
d
so
t
h
a
t
we
d
o
n
'
t
g
e
t
b
in
d
to
th
e
o
ri
g
i
n
a
l
ima
g
e
,
a
n
d
f
o
r
o
u
r
a
tt
a
c
k
we
c
h
o
se
c
o
m
p
re
ss
io
n
j
o
in
t
p
h
o
to
g
ra
p
h
ic
e
x
p
e
rts
g
r
o
u
p
(JPE
G
)
c
o
m
p
re
ss
io
n
b
e
c
a
u
se
it
’s
th
e
m
o
st
u
se
d
m
e
th
o
d
fo
r
ima
g
e
a
n
d
v
i
d
e
o
s
c
o
m
p
re
ss
io
n
a
lo
n
g
with
si
n
g
u
lar
v
a
lu
e
d
e
c
o
m
p
o
siti
o
n
(S
VD
)
to
m
a
k
e
o
u
r
m
a
rk
a
s
ro
b
u
st
a
s
p
o
ss
ib
le.
An
d
th
e
re
su
lt
s
we
g
a
in
fro
m
o
u
r
m
e
th
o
d
a
re
p
ro
m
isin
g
a
n
d
it
d
i
d
g
iv
e
a
s h
ig
h
q
u
a
li
t
y
d
ig
it
a
l
wa
term
a
rk
in
g
.
K
ey
w
o
r
d
s
:
Dig
ital w
ater
m
ar
k
Hy
b
r
id
I
m
ag
e
p
r
o
ce
s
s
in
g
I
n
v
is
ib
le
J
PEG
L
SB
-
wate
r
m
ar
k
in
g
SVD
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
Nasr
E
d
d
in
e
T
o
u
ati
I
n
f
o
r
m
atio
n
Pro
ce
s
s
in
g
an
d
T
elec
o
m
m
u
n
icatio
n
L
ab
o
r
ato
r
y
(
L
T
I
T
)
,
Facu
lty
o
f
T
ec
h
n
o
lo
g
y
Un
iv
er
s
ity
T
AHRI
Mo
h
am
m
e
d
B
ec
h
ar
B
ec
h
ar
,
Alg
er
ia
E
m
ail:
to
u
ati.
n
asre
d
d
in
e
.
d
z@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
Dig
ital
wate
r
m
ar
k
in
g
is
an
im
ag
e
p
r
o
ce
s
s
g
r
o
u
n
d
e
d
o
n
i
m
ag
e
m
an
ip
u
latio
n
s
to
allo
ws
u
s
to
ad
d
s
o
m
e
in
f
o
r
m
atio
n
we
c
h
o
s
e
t
o
o
u
r
im
ag
e
with
v
is
ib
le
o
r
i
n
v
is
ib
le
way
an
d
th
at
d
e
p
en
d
o
n
th
e
u
s
e
o
f
th
at
in
f
o
r
m
atio
n
,
th
er
e
two
m
ajo
r
u
s
es
f
o
r
d
ig
ital
wate
r
m
a
r
k
in
g
,
f
ir
s
t
im
ag
e
au
t
h
en
ticatio
n
a
n
d
im
ag
e
d
ata
h
id
in
g
.
T
h
e
p
u
r
p
o
s
e
o
f
im
ag
e
au
th
e
n
ticatio
n
is
f
o
r
d
etec
tin
g
m
alici
o
u
s
m
an
ip
u
latio
n
,
b
u
t
th
ese
o
l
d
m
eth
o
d
s
co
n
s
id
e
r
s
o
m
e
o
th
er
im
ag
e
m
an
ip
u
lati
o
n
s
as
attac
k
s
lik
e
co
m
p
r
ess
i
o
n
an
d
im
ag
e
en
h
an
ce
m
en
t,
an
d
th
e
p
u
r
p
o
s
e
o
f
im
ag
e
d
ata
h
id
in
g
is
to
em
b
ed
a
s
ec
r
et
in
f
o
r
m
atio
n
with
in
t
h
e
co
v
er
im
ag
e
as
lar
g
e
as
p
o
s
s
ib
le
with
m
in
im
al
d
eg
r
ad
atio
n
f
o
r
th
e
co
v
e
r
im
ag
e.
T
h
e
r
ef
o
r
e
,
d
ig
ital
wate
r
m
ar
k
in
g
h
av
e
two
im
p
o
r
tan
t
p
ar
ts
f
o
r
it
to
b
e
co
n
s
id
er
a
p
r
ac
tical
o
n
e
wh
ic
h
is
in
v
is
ib
ilit
y
with
o
u
t
d
estr
o
y
in
g
t
h
e
v
is
u
al
p
r
o
p
e
r
ties
an
d
th
e
r
o
b
u
s
tn
ess
o
f
th
e
d
ig
ital
wate
r
m
ar
k
[
1]
-
[
3
]
.
Ou
r
tech
n
iq
u
e
is
q
u
a
n
tizatio
n
co
ef
f
icien
ts
-
b
ased
m
an
n
e
r
a
n
d
f
o
r
th
o
s
e
r
eq
u
ir
em
e
n
t
we
ar
e
u
s
in
g
least
s
ig
n
if
ican
t
b
its
wate
r
m
ar
k
in
g
(
L
SB
-
wate
r
m
ar
k
i
n
g
)
b
u
t th
e
ea
r
lier
m
eth
o
d
s
r
eq
u
ir
es
an
en
cr
y
p
tio
n
with
a
k
ey
s
o
ev
en
if
t
h
ey
d
o
n
’
t
n
ee
d
th
e
o
r
ig
in
al
im
ag
e
th
ey
’
r
e
s
till
b
in
d
to
th
e
k
ey
w
h
ich
th
e
y
ca
n
’
t
ex
tr
ac
t
th
e
m
ar
k
if
t
h
ey
lo
s
t
it,
h
o
wev
er
o
u
r
tech
n
iq
u
e
wo
r
k
in
s
m
ar
te
r
wh
y
wh
ic
h
d
o
n
’
t
n
ee
d
th
e
o
r
ig
in
al
im
ag
e
o
r
a
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
S
elf
emb
ed
d
in
g
d
ig
ita
l wa
terma
r
k
u
s
in
g
h
yb
r
id
meth
o
d
a
g
a
i
n
s
t c
o
mp
r
ess
io
n
a
tta
ck
(
N
a
s
r
E
d
d
in
e
To
u
a
ti
)
865
en
cr
y
p
tio
n
f
o
r
th
e
m
ar
k
b
ef
o
r
e
em
b
ed
d
in
g
s
o
n
o
m
o
r
e
n
ee
d
f
o
r
th
e
k
ey
an
d
p
r
o
v
id
e
th
e
least d
is
to
r
tio
n
o
n
o
u
r
co
v
er
im
ag
e
with
th
e
m
o
s
t secu
r
ed
way
.
T
h
e
r
ef
o
r
e
,
as lo
n
g
a
s
we
h
av
e
th
e
p
r
o
p
er
eq
u
ip
m
e
n
t a
n
d
s
o
f
twar
e
we
will b
e
ab
le
to
em
b
e
d
an
d
ex
tr
ac
t
th
e
d
ig
ital w
ater
m
ar
k
with
o
u
t p
r
o
b
lem
.
T
h
is
q
u
an
tizatio
n
co
e
f
f
icien
ts
-
b
ased
tech
n
i
q
u
e
with
th
e
h
elp
o
f
s
in
g
u
lar
v
alu
e
d
ec
o
m
p
o
s
itio
n
(
SVD)
is
f
o
r
s
elf
-
em
b
ed
d
i
n
g
d
ig
ital
wate
r
m
ar
k
wh
e
n
ev
er
th
er
e
a
jo
in
t
p
h
o
to
g
r
a
p
h
ic
ex
p
er
ts
g
r
o
u
p
(
J
PEG)
attac
k
(
co
m
p
r
ess
io
n
d
ec
o
m
p
r
ess
io
n
)
is
ap
p
lied
a
n
d
its
will
b
e
e
m
b
ed
d
e
d
in
all
th
e
L
SB
b
its
f
o
r
m
o
r
e
e
f
f
icien
cy
.
An
d
f
o
r
s
u
ch
r
esu
lts
we
wate
r
m
ar
k
t
h
e
q
u
an
tizatio
n
c
o
ef
f
i
cien
ts
with
8
x
8
m
ar
k
,
an
d
wh
en
th
e
q
u
an
tizatio
n
o
n
th
e
d
is
cr
ete
co
s
in
e
tr
an
s
f
o
r
m
(
DC
T
)
is
ap
p
lied
th
e
m
ar
k
w
ill
b
e
em
b
ed
d
ed
alo
n
g
s
id
e
it
o
n
th
e
co
v
e
r
im
ag
e
u
s
in
g
th
e
co
ef
f
icien
ts
,
b
u
t
in
n
o
r
m
al
p
atter
n
way
th
e
d
is
to
r
t
io
n
s
will
b
e
h
ig
h
b
ec
au
s
e
we
ar
e
u
s
in
g
th
e
8
th
b
it
in
ea
ch
co
ef
f
icien
t
to
cr
ea
te
a
r
o
b
u
s
t
d
ig
ital
wate
r
m
ar
k
o
n
t
h
e
q
u
an
tizatio
n
co
e
f
f
icien
ts
an
d
th
at
will
lead
to
m
ajo
r
d
is
to
r
tio
n
s
all
o
v
er
th
e
co
v
er
an
d
also
c
o
u
ld
lead
to
m
ak
e
th
e
d
ig
ital
wate
r
m
ar
k
to
b
e
v
is
ib
le,
SVD
m
eth
o
d
p
r
o
v
id
e
a
m
an
i
p
u
lati
o
n
th
at
ca
n
h
elp
u
s
to
p
r
e
v
e
n
t
th
is
p
r
o
b
lem
b
y
cr
ea
tin
g
a
co
ef
f
icien
ts
with
em
b
ed
d
e
d
d
ig
ital
wate
r
m
a
r
k
o
n
t
h
e
8
th
b
it
f
o
r
t
h
e
m
o
s
t
r
o
b
u
s
tn
ess
an
d
also
as
in
v
is
ib
le
as
p
o
s
s
ib
le.
T
o
b
e
m
o
r
e
s
p
ec
if
ic
o
u
r
SVD
-
DC
T
h
y
b
r
id
tech
n
iq
u
e
wo
r
k
as self
-
em
b
ed
d
in
g
d
ig
ital w
ater
m
ar
k
,
b
y
im
p
lem
en
tin
g
it
as a
s
leep
in
g
p
ar
am
eter
t
h
at
g
et
ac
tiv
ated
in
ca
s
e
o
f
J
PEG
c
o
m
p
r
ess
io
n
attac
k.
2.
RE
VI
E
W
O
F
RE
L
A
T
E
D
W
O
RK
S
I
n
th
e
p
ast
y
ea
r
s
d
ig
ital
im
a
g
es
wate
r
m
ar
k
in
g
d
e
v
elo
p
e
d
q
u
ite
d
r
am
atica
lly
,
an
d
th
er
e'
s
s
o
m
an
y
m
eth
o
d
s
an
d
tec
h
n
iq
u
e
f
o
r
th
a
t [
4
]
,
[
5
]
,
a
n
d
its
ch
an
g
e
f
r
o
m
a
d
o
m
ain
to
an
o
th
e
r
m
ed
ical
,
t
elec
o
m
m
u
n
icatio
n
,
co
p
y
r
ig
h
t
r
e
g
is
tr
atio
n
to
j
u
s
t
s
im
p
le
ef
f
ec
t
f
o
r
im
a
g
es
an
d
v
id
eo
s
[
6
]
-
[
8
]
,
b
u
t
ea
c
h
o
n
e
o
f
th
em
n
ee
d
s
o
m
e
p
ar
am
eter
s
lik
e
o
r
ig
in
al
im
ag
e
o
r
a
k
ey
to
ex
tr
ac
t
th
e
d
ig
ita
l
wate
r
m
ar
k
co
r
r
ec
tly
[
9
]
-
[
1
1
]
,
wh
ich
m
ea
n
a
b
ig
p
r
o
b
lem
in
ca
s
e
lo
s
e
o
r
d
estro
y
th
is
p
ar
am
eter
s
,
th
at
will
l
ea
d
to
in
ca
p
ab
ilit
y
f
o
r
th
e
e
x
tr
ac
tio
n
[
1
2
]
-
[
1
4
]
,
i
n
o
th
er
wo
r
d
s
em
b
ed
d
in
g
a
m
ar
k
in
th
e
L
SB
o
f
im
ag
es
with
s
im
p
le
m
eth
o
d
s
alo
n
e,
an
d
n
o
t
u
s
in
g
an
y
en
cr
y
p
tio
n
s
o
r
o
t
h
er
d
ata
h
id
in
g
tech
n
iq
u
es
is
to
o
f
r
a
g
ile
f
o
r
b
e
u
s
ed
alo
n
e
to
co
u
n
ter
an
y
k
i
n
d
o
f
d
ata
m
an
ip
u
latio
n
[
1
5
]
,
[
1
6
]
.
B
u
t
in
th
is
p
ap
er
we
p
r
o
p
o
s
e
a
s
o
lu
tio
n
f
o
r
th
is
p
r
o
b
lem
,
b
y
cr
e
atin
g
a
m
eth
o
d
t
o
em
b
ed
a
d
ig
ital
wate
r
m
ar
k
,
a
n
d
ex
tr
ac
tin
g
it
af
ter
r
eg
a
r
d
less
f
o
r
th
e
n
ee
d
f
o
r
a
n
y
o
th
er
p
ar
am
eter
s
u
s
in
g
an
y
s
tan
d
ar
d
L
SB
ex
tr
ac
tin
g
m
eth
o
d
to
g
et
th
e
wate
r
m
ar
k
.
3.
RE
Q
UIR
E
D
K
NO
W
L
E
DG
E
3
.
1
.
SVD
Sin
g
u
lar
v
alu
e
d
ec
o
m
p
o
s
itio
n
(
SVD
)
is
n
u
m
er
ical
an
aly
s
is
m
eth
o
d
u
s
ed
to
an
al
y
ze
m
at
r
ices
with
m
u
ltip
le
ap
p
licatio
n
,
with
th
is
tech
n
iq
u
e
we
ca
n
d
ec
o
m
p
o
s
e
a
m
atr
ix
th
r
ee
m
atr
ices
with
t
h
e
s
am
e
s
ize
as
th
e
o
r
ig
in
al
m
atr
ix
[
1
7
]
,
[
1
8
]
,
wh
er
e
th
e
U
a
n
d
V
co
m
p
o
n
en
ts
a
r
e
×
r
ea
l
u
n
itar
y
m
atr
ice
s
with
s
m
all
s
in
g
u
lar
v
alu
es,
an
d
th
e
S
co
m
p
o
n
en
t
is
an
×
d
iag
o
n
al
m
atr
i
x
with
lar
g
er
s
in
g
u
lar
v
al
u
e
en
t
r
ies
wh
ich
s
atis
f
y
(
1
,
1
)
⩾
(
1
,
2
)
⩾
(
1
,
3
)
⩾
(
1
,
4
)
[
1
9
]
.
B
is
th
e
r
ec
o
n
s
tr
u
cted
m
atr
ix
af
ter
th
e
i
n
v
er
s
e
SVD
tr
an
s
f
o
r
m
atio
n
is
ap
p
lied
B
=
×
×
.
[
1
9
]
s
u
ch
as f
o
r
t
h
e
m
atr
ix
A:
A
=
(
1
2
3
4
5
6
7
8
9
)
an
d
[
U,
S,
V]
=
SVD
(
A)
,
is
:
U
=
(
−
0
.
21483724
0
.
88723069
0
.
40824829
−
0
.
52058739
0
.
24964395
−
0
.
81649658
−
0
.
82633754
−
0
.
3879427
8
0
.
40824829
)
,
S =
(
1
.
68481034
+
01
0
0
0
1
.
06836951
+
00
0
0
0
4
.
41842475
−
16
)
,
V
=
(
−
0
.
47967118
−
0
.
57236779
−
0
.
66506441
−
0
.
77669099
−
0
.
07568647
0
.
62531805
−
0
.
40824829
0
.
81649658
−
0
.
40824829
)
,
an
d
B
=
×
×
3
.
2
.
J
P
E
G
J
PEG
m
eth
o
d
m
ain
ly
co
n
s
is
ts
o
f
th
r
ee
s
tep
s
,
n
am
ely
DC
T
,
q
u
an
tizer
,
an
d
en
tr
o
p
y
en
co
d
e
r
.
Firstl
y
,
we
ap
p
ly
two
-
d
im
e
n
s
io
n
al
D
C
T
to
th
e
n
o
n
-
o
v
er
la
p
p
in
g
8
×8
b
lo
ck
s
,
th
is
s
tep
will
tr
an
s
f
o
r
m
ed
t
h
e
o
r
ig
i
n
al
im
ag
e
f
r
o
m
t
h
e
s
p
atial
d
o
m
ai
n
to
th
e
f
r
eq
u
en
cy
d
o
m
ain
.
S
ec
o
n
d
ly
th
e
o
b
tain
ed
DC
T
co
ef
f
icien
ts
ar
e
th
en
tr
e
ated
with
th
e
p
r
ed
eter
m
i
n
ed
q
u
an
tizatio
n
c
o
ef
f
icien
t
a
n
d
q
u
a
n
tized
.
T
h
ir
d
ly
we
will
co
o
r
d
in
ate
th
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
24
,
No
.
2
,
No
v
em
b
er
2
0
2
1
:
86
4
-
8
70
866
q
u
an
tized
DC
T
co
ef
f
icien
ts
with
zig
za
g
s
ca
n
n
in
g
o
r
d
er
a
n
d
af
ter
th
at
r
u
n
len
g
th
en
co
d
in
g
(
R
L
E
)
af
ter
all
th
is
we
g
et
th
e
co
m
p
r
ess
ed
in
f
o
r
m
atio
n
,
an
d
f
o
r
r
ec
o
n
s
tr
u
ctin
g
th
e
in
f
o
r
m
atio
n
we
n
ee
d
to
g
o
in
r
e
v
er
s
e
f
o
r
all
th
e
s
tep
s
[
1
2
]
-
[
2
1
]
.
T
h
e
two
-
d
im
en
s
io
n
al
DC
T
:
2
√
(
)
(
)
(
)
∑
∑
−
1
=
0
−
1
=
0
(
,
)
(
2
+
1
)
2
(
2
+
1
)
2
(
1
)
wh
er
e:
C
(
m
)
,
C
(
n
)
=
1
√
2
⁄
f
o
r
m
,
n
=0
an
d
C
(
m
)
,
C
(
n
)
=
1
o
th
e
r
wis
e.
T
h
e
in
v
er
s
e
two
-
d
im
en
s
io
n
al
D
C
T
:
2
√
(
)
∑
∑
−
1
=
0
−
1
=
0
(
)
(
)
(
,
)
(
2
+
1
)
2
(
2
+
1
)
2
(
2
)
wh
er
e
an
d
C
(
m
)
,
C
(
n
)
=
1
√
2
⁄
f
o
r
m
,
n
=0
an
d
C
(
m
)
,
C
(
n
)
=1
o
th
er
wi
s
e.
F (
m
,
n
)
is
th
e
DC
T
o
f
t
h
e
s
ig
n
al
f
(
x
,
y
)
3
.
2
.
L
SB
L
SB
-
wate
r
m
ar
k
in
g
m
eth
o
d
is
u
s
ed
f
o
r
f
r
e
q
u
en
t
p
r
o
ce
s
s
es
to
em
b
ed
in
f
o
r
m
atio
n
i
n
a
co
v
er
im
ag
e,
th
at
we
ch
an
g
e
th
e
in
s
id
e
o
f
a
co
v
er
im
ag
e
p
ix
els
b
y
b
its
o
f
t
h
e
s
ec
r
et
m
ess
ag
e.
W
e
ch
an
g
e
th
e
f
ir
s
t
b
its
f
r
o
m
th
e
co
v
er
im
ag
e,
with
t
h
e
b
it
s
o
f
o
u
r
s
e
cr
et
m
ess
ag
e
d
ep
e
n
d
in
g
o
n
th
e
n
ee
d
e
d
ch
a
n
g
es
ac
co
r
d
in
g
to
th
e
em
b
ed
d
e
d
m
ess
ag
e.
Usu
ally
o
n
ly
th
e
f
ir
s
t
h
alf
o
f
th
e
b
its
o
f
ea
ch
p
i
x
el
f
r
o
m
th
e
co
v
e
r
im
ag
e
n
ee
d
ed
to
b
e
r
ep
lace
d
with
s
ec
r
et
m
ess
ag
e
b
its
b
ec
au
s
e
it’s
o
n
ly
n
ee
d
ed
lo
w
b
its
f
o
r
em
b
ed
d
in
g
th
e
s
e
cr
et
m
ess
ag
e.
I
n
Fig
u
r
e
1
,
an
d
th
is
ad
ju
s
tm
en
ts
will
r
esu
lt
in
lo
w
ch
a
n
g
es
in
in
ten
s
ity
o
f
t
h
e
co
lo
r
s
b
u
t
it
wi
ll
n
o
t
b
e
n
o
ticea
b
l
e
f
o
r
th
e
h
u
m
a
n
ey
es [
2
]
,
[
2
2
]
,
[
2
3
]
.
Fig
u
r
e
1
.
An
ex
am
p
le
o
f
3
rd
b
i
t L
SB
4.
P
RO
P
O
SE
D
M
E
T
H
O
D
T
h
is
s
ec
tio
n
is
f
o
r
d
escr
ib
in
g
o
u
r
tech
n
iq
u
e,
we
ar
e
wate
r
m
ar
k
in
g
th
e
q
u
a
n
tizatio
n
co
ef
f
i
cien
ts
(
Q)
f
o
r
th
e
DC
T
with
8
x
8
im
ag
e
to
g
et
th
e
Qw,
th
en
we
ap
p
lies
th
e
SVD
o
n
b
o
u
g
h
t
o
f
th
e
co
e
f
f
icien
ts
Q
an
d
Qw
to
g
et
th
e
f
allo
win
g
m
atr
ix
Uq
,
Sq
,
Vq
f
r
o
m
Q,
an
d
Uq
w,
Sq
w,
Vq
w
f
r
o
m
Qcw
.
th
en
w
e
u
s
e
th
e
Sq
w
an
d
r
ev
er
s
ed
th
e
SVD
with
Uq
an
d
Vq
T
to
r
ec
r
ea
te
a
n
ew
c
o
ef
f
icien
ts
m
atr
ix
as
lik
e
s
h
o
wn
in
th
e
(
3
)
.
An
d
t
h
is
m
eth
o
d
g
iv
es
u
s
an
o
th
er
p
r
o
p
er
ty
,
th
at
wh
en
th
e
m
o
r
e
th
e
l
o
wer
o
f
th
e
q
u
an
tizatio
n
q
u
ality
th
e
m
o
r
e
r
o
b
u
s
t
th
e
d
ig
ital
wate
r
m
ar
k
a
n
d
b
e
h
av
e
with
s
elf
-
em
b
e
d
d
in
g
o
n
all
o
v
er
th
e
o
r
ig
in
al
im
a
g
e,
an
d
th
e
th
a
n
k
s
is
to
wate
r
m
ar
k
in
g
o
n
th
e
8
th
b
it
an
d
th
at
wh
y
it’s p
e
r
f
ec
t f
o
r
co
u
n
ter
in
g
J
PEG
attac
k
s
.
[
Uq
,
Sq
,
Vq
]
=
SVD
(
Q)
[
Uq
w,
Sq
w,
Vq
w]
=
SVD
(
Q
w)
(
3
)
NQw
=
[
Uq
w×
Sq
×
Vq
wT
]
Af
ter
th
at
we
co
n
tin
u
e
in
o
u
r
co
m
p
r
ess
io
n
an
d
ap
p
lied
th
e
DC
T
o
n
ea
ch
8
x
8
b
lo
ck
o
f
th
e
co
v
e
r
im
ag
e,
th
e
d
ig
ital
wate
r
m
ar
k
will
b
e
em
b
ed
d
ed
au
to
m
atic
ally
in
all
th
e
8
x
8
b
lo
ck
s
o
f
th
e
co
v
er
,
we
will
n
o
tice
th
er
e
a
litt
le
d
if
f
er
e
n
t
i
n
th
e
p
o
s
itio
n
in
g
ab
o
u
t
th
e
wa
ter
m
ar
k
b
its
with
a
ch
an
g
e
o
n
b
o
u
g
h
t
ax
es
X
an
d
Y
eq
u
al
to
(
-
1,
-
1
)
c
o
m
p
ar
e
d
t
o
th
e
o
r
ig
in
al
af
ter
ex
tr
ac
tio
n
.
Fig
u
r
e
s
2
(
a
)
an
d
2
(
b
)
,
an
d
t
h
at
b
ec
au
s
e
o
f
th
e
DC
T
.
An
d
o
n
th
e
o
p
p
o
s
ite
o
f
o
th
e
r
tech
n
iq
u
es,
we
d
o
n
’
t
n
ee
d
a
n
y
o
th
er
p
ar
a
m
eter
s
to
ex
tr
ac
t
t
h
e
d
i
g
ital
wate
r
m
ar
k
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
S
elf
emb
ed
d
in
g
d
ig
ita
l wa
terma
r
k
u
s
in
g
h
yb
r
id
meth
o
d
a
g
a
i
n
s
t c
o
mp
r
ess
io
n
a
tta
ck
(
N
a
s
r
E
d
d
in
e
To
u
a
ti
)
867
(
a
)
(
b
)
Fig
u
r
e
2
.
T
h
e
u
s
ed
im
a
g
e
f
o
r
wate
r
m
ar
k
in
g
:
(
a
)
o
r
i
g
in
al
wate
r
m
ar
k
a
n
d
(
b
)
th
e
e
x
tr
ac
ted
m
ar
k
4
.
1
.
E
m
bedd
ing
pro
ce
s
s
I
n
th
is
s
ec
tio
n
,
we
p
r
esen
t
o
u
r
em
b
ed
d
in
g
m
eth
o
d
.
Fig
u
r
e
3
,
a
q
u
a
n
tizatio
n
co
ef
f
ic
ien
ts
-
b
ased
wate
r
m
ar
k
in
g
s
ch
em
e.
B
o
th
t
h
e
em
b
ed
d
i
n
g
p
r
o
ce
d
u
r
e
an
d
ex
tr
ac
tin
g
p
r
o
ce
d
u
r
e
ar
e
in
clu
d
ed
.
T
h
e
o
v
er
v
iew
o
f
th
e
p
r
o
p
o
s
ed
d
ig
ital w
ater
m
ar
k
in
g
s
ch
em
e
is
s
h
o
wn
.
Fig
u
r
e
3
.
Diag
r
a
m
o
f
q
u
a
n
tizatio
n
co
ef
f
icien
t
m
eth
o
d
5.
RE
SU
L
T
AND
DI
SCUS
SI
O
N
I
n
o
u
r
ex
p
er
im
en
tal
r
esu
lts
,
a
5
1
2
x
5
1
2
g
r
ay
s
ca
le
im
ag
e
wh
i
ch
is
s
h
o
wn
in
Fig
u
r
e
4
(
a
)
we
r
e
u
s
ed
as
co
v
er
im
ag
e
.
wh
en
,
we
e
m
b
e
d
th
e
s
ec
r
et
d
ata
wh
ich
c
o
n
tai
n
o
u
r
wate
r
m
ar
k
‘
letter
T
’
,
w
e
g
o
t
a
wate
r
m
ar
k
ed
im
ag
e
with
o
u
t
Fig
u
r
e
s
4
(b
)
-
(
f
)
n
o
ticea
b
le
d
is
to
r
tio
n
in
ca
s
e
o
f
h
i
g
h
er
q
u
a
n
tizatio
n
co
e
f
f
ici
en
t
q
u
ality
an
d
th
e
lo
wer
th
e
q
u
ality
th
e
m
o
r
e
th
e
d
ig
ital
wate
r
m
ar
k
b
ec
o
m
e
r
o
b
u
s
t
tell
it
o
v
er
wh
elm
th
e
m
o
s
t
s
ig
n
if
ican
t
b
its
(
MSB
)
v
alu
es.
Fig
u
r
e
s
4
(
b
)
-
(
i)
r
ep
r
esen
t
th
e
d
ig
ital
wate
r
m
ar
k
ed
im
ag
es
with
b
o
u
g
h
t
s
tan
d
a
r
d
an
d
o
u
r
m
eth
o
d
tech
n
iq
u
es
with
t
h
e
s
am
e
q
u
a
n
tizatio
n
co
ef
f
icien
ts
v
alu
es,
an
d
we
ca
n
s
ee
th
e
d
if
f
er
en
t
r
ep
r
esen
t
in
t
h
e
less
d
is
to
r
tio
n
f
o
r
th
e
p
r
o
p
o
s
ed
m
e
th
o
d
.
An
d
we
n
o
tice
th
e
wate
r
m
ar
k
wo
r
k
lik
e
d
ef
e
n
s
e
tech
n
iq
u
e
ag
ain
s
t
J
PEG
attac
k
an
d
,
wh
er
e
it
is
b
ec
o
m
e
m
o
r
e
a
n
d
m
o
r
e
r
o
b
u
s
t
an
d
v
is
ib
le
ea
ch
tim
e
we
lo
w
er
th
e
q
u
an
tizatio
n
co
ef
f
icien
t
s
v
alu
es,
we
n
o
tice
in
Fig
u
r
e
4
(
b
)
with
Q=
9
0
,
th
at
th
e
d
ig
ital
wate
r
m
ar
k
o
n
th
e
8
th
b
its
is
co
m
p
letely
in
v
is
ib
le
an
d
th
er
e
n
o
n
o
ticea
b
le
d
is
to
r
tio
n
with
o
u
r
m
eth
o
d
wh
ile
in
Fig
u
r
e
4
(
c)
with
Q=
9
0
th
e
d
is
r
o
tio
n
is
c
o
m
p
letely
v
is
ib
le
,
an
d
Fig
u
r
e
4
(
d
)
wi
th
Q=
8
5
i
ts
s
im
ilar
to
Fig
u
r
e
4
(
b
)
w
h
ile
u
s
in
g
o
u
r
m
eth
o
d
,
wh
ile
Fig
u
r
e
4
(
e
)
g
et
m
o
r
e
d
e
s
to
r
ed
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
24
,
No
.
2
,
No
v
em
b
er
2
0
2
1
:
86
4
-
8
70
868
Me
an
wh
ile
o
u
r
n
ew
d
ig
ital
w
ater
m
ar
k
in
g
m
eth
o
d
in
Fig
u
r
e
4
(
f
)
with
Q
=7
5
is
b
etter
th
a
n
th
e
n
o
r
m
al
m
eth
o
d
in
Fig
u
r
e
4
(
g
)
with
th
e
s
am
e
Q,
th
e,
n
o
r
m
al
d
i
g
ital
wate
r
m
ar
k
d
ea
lt
a
g
r
ea
t
d
is
to
r
tio
n
o
n
th
e
co
v
er
im
ag
e,
an
d
ev
en
m
o
r
e
o
n
lo
w
er
q
u
an
tizatio
n
co
ef
f
icien
ts
v
alu
es,
b
u
t
ev
en
in
lo
wer
v
alu
es
in
Q
o
u
r
m
eth
o
d
s
till
b
etter
a
nd
th
at
is
m
a
n
if
ested
in
Fig
u
r
e
4
(
h
)
with
Q=
3
5
i
t’
s
a
l
ittl
e
b
it
clea
r
e
r
th
e
n
Fig
u
r
e
4
(
i)
with
Q=
3
5
.
T
h
e
q
u
ality
o
f
ea
ch
g
o
o
d
r
esto
r
ed
im
ag
e
is
p
r
o
v
id
e
d
in
T
a
b
le
1.
(
a
)
(
b
)
(
c
)
(
d
)
(
e
)
(
f
)
(
g
)
(
h
)
(
i
)
Fig
u
r
e
4
.
T
h
e
o
r
i
g
in
al
im
ag
e
c
o
m
p
ar
ed
to
wate
r
m
ar
k
ed
im
ag
es
:
(
a)
o
r
ig
in
al
,
(
b
)
n
ew
wate
r
m
ar
k
ed
Q=
9
0
,
(
c)
n
o
r
m
al
wate
r
m
ar
k
e
d
Q=
9
0
,
(
d
)
n
ew
wate
r
m
ar
k
e
d
Q=
8
5
,
(
e)
n
o
r
m
al
wate
r
m
ar
k
e
d
Q=
8
5
,
(f)
n
ew
wate
r
m
a
r
k
ed
Q=
7
5
,
(
g
)
n
o
r
m
al
wate
r
m
ar
k
e
d
Q=
7
5
,
(
h
)
n
ew
wate
r
m
ar
k
ed
Q=
3
5
,
an
d
(
i)
n
o
r
m
al
wate
r
m
ar
k
e
d
Q=
3
5
T
h
e
s
tr
u
ctu
r
al
s
im
ilar
ity
(
SS
I
M)
in
d
ex
q
u
ality
ass
ess
m
en
t
i
n
d
ex
is
th
e
r
atio
n
o
f
th
e
co
m
p
u
tatio
n
o
f
th
r
ee
ter
m
s
,
n
am
ely
t
h
e
co
n
tr
ast
ter
m
,
th
e
lu
m
in
an
ce
ter
m
an
d
t
h
e
s
tr
u
ctu
r
al
ter
m
.
T
h
e
o
v
er
all
i
n
d
ex
is
a
m
u
ltip
licativ
e
co
m
b
in
atio
n
o
f
th
e
th
r
ee
ter
m
s
[
2
4
]
.
SS
I
M(
x
,
y
)
=
[
l(
x
,
y
)
]
α
⋅
[
c(
x
,
y
)
]
β
⋅
[
s
(
x
,
y
)
]
γ
\
(
4
)
wh
er
e:
(
,
)
=
2
µ
µ
+
C
1
µ
2
+
µ
2
+
C
1
,
(
,
)
=
2
σ
σ
+
C
2
σ
2
+
σ
2
+
C
2
,
(
,
)
=
σ
+
C
3
σ
σ
+
C
3
(
5
)
T
ab
le
1
.
T
h
e
p
ea
k
s
ig
n
al
-
to
-
n
o
is
e
r
atio
(
PS
NR
)
an
d
m
ea
n
s
tr
u
ctu
r
al
s
im
ilar
ity
(
MSSI
M)
v
alu
e
o
f
ea
c
h
r
ec
o
n
s
tr
u
cted
im
ag
e
Q
u
a
n
t
i
z
a
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
P
S
N
R
(
d
B
)
M
S
S
I
M
Q
=
9
0
3
3
.
8
9
0
.
9
2
6
2
Q
=
8
5
3
2
.
6
8
0
.
8
8
0
1
Q
=
8
0
3
0
.
8
1
0
.
8
0
3
7
Q
=
7
5
2
9
.
6
3
0
.
7
3
2
6
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci
I
SS
N:
2502
-
4
7
5
2
S
elf
emb
ed
d
in
g
d
ig
ita
l wa
terma
r
k
u
s
in
g
h
yb
r
id
meth
o
d
a
g
a
i
n
s
t c
o
mp
r
ess
io
n
a
tta
ck
(
N
a
s
r
E
d
d
in
e
To
u
a
ti
)
869
I
n
th
e
ex
tr
ac
tio
n
we
o
b
v
io
u
s
ly
d
o
n
’
t
n
ee
d
all
th
e
d
ig
ital
wate
r
m
ar
k
s
with
em
b
ed
in
all
th
e
co
v
er
we
o
n
ly
n
ee
d
o
n
e,
s
o
we
ex
tr
ac
t
all
th
e
L
S
B
f
r
o
m
th
e
im
ag
e
th
en
we
r
u
n
8
x
8
s
ize
co
n
to
u
r
s
ca
n
n
er
to
d
etec
t
th
e
d
ig
ital
wate
r
m
ar
k
lik
e
Fig
u
r
e
s
5
(
a)
-
(
e)
.
L
ik
e
wh
at
we
a
r
e
n
o
ticin
g
th
er
e
is
a
lo
w
-
q
u
ality
e
x
tr
ac
tio
n
ca
s
es,
b
u
t
it
s
till
r
ec
o
g
n
izab
le
an
d
f
o
r
th
at
we
ad
d
a
th
r
esh
o
l
d
to
o
u
r
8
x
8
co
n
t
o
u
r
s
ca
n
n
er
to
co
n
s
id
e
r
ev
er
y
ca
s
e
ab
o
v
e
8
0
% a
s
a
v
alid
r
esu
lt T
ab
le
2
.
(
a)
(
b
)
(
c)
(
d
)
(
e)
Fig
u
r
e
5
.
T
h
e
ex
tr
ac
ted
wate
r
m
ar
k
:
(
a)
b
est
ex
tr
ac
tio
n
ca
s
e
,
(
b
)
m
e
d
iu
m
ex
tr
ac
tio
n
ca
s
e
,
(
c)
m
ed
iu
m
ex
tr
ac
tio
n
ca
s
e
,
(
d
)
m
ed
iu
m
e
x
tr
ac
tio
n
ca
s
e
,
a
n
d
(
e)
lo
wer
ex
t
r
ac
tio
n
ca
s
e
R
ec
o
n
s
tr
u
cted
m
ag
es
ar
e
e
v
al
u
ated
b
y
th
e
p
ea
k
s
ig
n
al
-
to
-
n
o
is
e
r
atio
PS
NR
,
it’s
th
e
m
o
s
t
c
o
m
m
o
n
l
y
u
s
ed
as a
m
ea
s
u
r
e
o
f
q
u
ality
f
o
r
im
ag
es c
o
m
p
r
ess
io
n
s
,
it
is
t
h
e
m
o
s
t e
asil
y
d
ef
in
ed
v
ia
th
e
m
ea
n
s
q
u
ar
ed
er
r
o
r
(
MSE
)
wh
ich
f
o
r
th
e
two
im
a
g
es
o
r
ig
in
al
an
d
th
e
r
ec
o
n
s
tr
u
cted
,
th
e
PS
NR
v
alu
e
ap
p
r
o
a
ch
es
in
f
in
ity
as
th
e
MSE
ap
p
r
o
ac
h
es
ze
r
o
;
th
is
m
e
an
s
h
ig
h
er
PS
NR
v
alu
e
p
r
o
v
id
es
a
h
ig
h
er
im
ag
e
q
u
ality
[
2
5
]
.
An
d
th
e
eq
u
atio
n
d
ef
in
ed
as
(
6
)
an
d
(
7
)
;
MSE
=
1
∑
∑
(
−
)
2
=
1
=
1
(
6
)
PS
NR
=
10
10
(
255
2
(
,
)
⁄
)
(
7
)
An
d
s
u
r
p
r
is
in
g
ly
o
u
r
m
eth
o
d
b
eh
av
e
th
e
s
am
e
wa
y
in
in
tr
a
n
s
m
is
s
io
n
ch
an
n
els wh
ich
m
e
an
lo
wer
th
e
c
h
an
n
el
q
u
ality
th
e
s
tr
o
n
g
er
th
e
r
o
b
u
s
tn
ess
o
f
o
u
r
m
ar
k
.
T
ab
le
2
.
T
h
r
esh
o
ld
a
n
d
PS
NR
o
f
th
e
ex
t
r
ac
ted
wate
r
m
ar
k
Ex
t
r
a
c
t
e
d
mar
k
Th
r
e
s
h
o
l
d
c
a
l
c
u
l
a
t
e
d
P
S
N
R
(
d
B
)
a
1
0
0
%
3
0
.
0
3
(
A
c
c
e
p
t
e
d
mar
k
)
b
9
3
.
3
%
2
9
.
1
1
(
A
c
c
e
p
t
e
d
mar
k
)
c
9
4
.
1
%
2
8
.
9
4
(
A
c
c
e
p
t
e
d
mar
k
)
d
7
1
.
2
2
%
2
7
.
5
6
(
R
e
j
e
c
t
e
d
m
a
r
k
)
6.
CO
NCLU
SI
O
N
th
is
p
ap
er
p
r
o
p
o
s
e
a
n
ew
h
y
b
r
id
d
ig
ital
im
ag
e
wate
r
m
ar
k
in
g
m
eth
o
d
b
ased
o
n
q
u
an
tizatio
n
co
ef
f
icien
t
an
d
s
in
g
u
lar
v
al
u
e
d
ec
o
m
p
o
s
itio
n
SVD,
wh
ich
h
elp
s
u
s
to
em
b
ed
a
d
i
g
ital
wate
r
m
ar
k
in
t
h
e
8
th
b
it
o
f
co
v
er
im
a
g
e
with
o
u
t
d
is
to
r
t
in
g
th
e
co
v
er
an
d
s
till
in
v
is
ib
l
e,
also
h
av
in
g
a
d
ef
en
s
iv
e
b
e
h
av
io
r
ag
ain
s
t
J
PEG
attac
k
th
at
th
e
d
ig
ital
wate
r
m
ar
k
b
ec
o
m
e
m
o
r
e
r
o
b
u
s
t
an
d
m
o
r
e
ag
g
r
ess
iv
e
tell
th
e
d
ig
ita
l
wate
r
m
ar
k
ch
a
n
g
e
th
e
p
o
s
itio
n
f
r
o
m
th
e
L
SB
to
t
h
e
m
o
s
t
s
ig
n
if
ican
t
b
its
(
MS
B
)
in
all
th
e
p
ix
els
o
f
th
e
co
v
er
an
d
b
ec
o
m
e
m
o
r
e
v
is
ib
le
to
h
u
m
an
ey
es
in
ca
s
e
o
f
b
ig
attac
k
s
.
An
d
in
ad
d
itio
n
it’s
b
eh
av
e
th
e
s
am
e
with
ch
an
n
el
n
o
is
es
s
u
r
p
r
is
in
g
ly
,
an
d
f
o
r
m
o
r
e
ef
f
icien
t
r
esu
lt
we
ar
e
lo
o
k
in
g
to
ad
d
a
m
ac
h
in
e
lear
n
in
g
s
e
ctio
n
to
o
b
tain
th
e
ch
an
g
in
g
p
atter
n
s
o
f
th
e
attac
k
s
to
p
r
ed
ict
f
u
t
u
r
es a
ttack
s
,
an
d
p
r
ep
a
r
e
a
m
o
r
e
ef
f
icien
t
way
to
co
u
n
ter
th
em
.
ACK
NO
WL
E
DG
E
M
E
NT
S
T
h
is
wo
r
k
is
s
u
p
p
o
r
ted
b
y
I
n
f
o
r
m
atio
n
Pr
o
ce
s
s
in
g
an
d
T
ele
co
m
m
u
n
icatio
n
L
ab
o
r
ato
r
y
(
L
T
I
T
)
.
RE
F
E
R
E
NC
E
S
[
1
]
S
.
D
.
L
i
n
,
S
.
C
.
S
h
i
e
,
a
n
d
J.
Y
.
G
u
o
,
“
I
m
p
r
o
v
i
n
g
t
h
e
r
o
b
u
s
t
n
e
s
s
o
f
D
C
T
-
b
a
s
e
d
i
m
a
g
e
w
a
t
e
r
m
a
r
k
i
n
g
a
g
a
i
n
s
t
J
P
E
G
c
o
m
p
r
e
s
s
i
o
n
,
”
C
o
m
p
u
t
e
r
S
t
a
n
d
a
r
d
s
&
I
n
t
e
r
f
a
c
es
,
v
o
l
.
3
2
,
n
o
.
1
-
2
,
p
p
.
5
4
-
6
0
,
J
u
n
.
2
0
1
0
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
s
i
.
2
0
0
9
.
0
6
.
0
0
4
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
5
0
2
-
4
7
5
2
I
n
d
o
n
esian
J
E
lec
E
n
g
&
C
o
m
p
Sci,
Vo
l.
24
,
No
.
2
,
No
v
em
b
er
2
0
2
1
:
86
4
-
8
70
870
[2
]
G
.
K.
Wallac
e
,
“
Th
e
JPE
G
stil
l
p
ictu
re
c
o
m
p
re
ss
io
n
sta
n
d
a
rd
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Co
n
s
u
m
e
r
El
e
c
tro
n
ics
,
v
o
l.
3
8
,
n
o
.
1
,
p
p
.
x
v
ii
i
–
x
x
x
i
v
,
F
e
b
.
1
9
9
2
,
d
o
i
:
1
0
.
1
1
0
9
/
3
0
.
1
2
5
0
7
2
.
[
3
]
N
.
A
l
i
a
s
a
n
d
F
e
r
d
a
E
r
n
a
w
a
n
,
“
M
u
l
t
i
p
l
e
w
a
t
e
rm
a
r
k
i
n
g
t
e
c
h
n
i
q
u
e
u
s
i
n
g
o
p
t
i
m
a
l
t
h
r
e
s
h
o
l
d
,
”
I
n
d
o
n
e
s
i
a
n
J
o
u
r
n
a
l
o
f
E
l
e
c
t
r
ic
a
l
E
n
g
i
n
e
e
r
i
n
g
a
n
d
C
o
m
p
u
t
e
r
S
c
ie
n
c
e
,
v
o
l
.
1
8
,
n
o.
1
,
p
p
.
3
6
8
-
3
7
6
,
A
p
r
.
2
0
2
0
,
d
o
i
:
1
0
.
1
1
5
9
1
/
i
j
e
e
c
s
.
v
1
8
.
i
1
.
p
p
3
6
8
-
376.
[4
]
A.
M
o
h
a
n
a
ra
th
i
n
a
m
,
S
.
Ka
m
a
lraj,
G
.
K.
D.
P
.
Ve
n
k
a
tes
a
n
,
R
.
V.
Ra
v
i
,
a
n
d
C.
S.
M
a
n
i
k
a
n
d
a
b
a
b
u
,
“
Dig
i
tal
wa
term
a
rk
in
g
tec
h
n
iq
u
e
s
fo
r
i
m
a
g
e
se
c
u
rit
y
:
a
re
v
iew
,
”
J
o
u
rn
a
l
o
f
Am
b
ien
t
In
telli
g
e
n
c
e
a
n
d
Hu
ma
n
ize
d
Co
mp
u
t
in
g
,
v
o
l
.
1
1
,
p
p
.
3
2
3
1
-
3
2
2
9
,
S
e
p
.
2
0
1
9
,
d
o
i:
1
0
.
1
0
0
7
/s
1
2
6
5
2
-
0
1
9
-
0
1
5
0
0
-
1.
[5
]
S
.
Ha
d
d
a
d
,
G
.
Co
a
tri
e
u
x
,
A
.
M
.
G
a
u
d
ry
,
a
n
d
M
ich
e
l
Co
z
ic,
“
Jo
i
n
t
Wate
rm
a
rk
in
g
-
E
n
c
ry
p
ti
o
n
-
JPE
G
-
LS
fo
r
M
e
d
ica
l
Im
a
g
e
Re
li
a
b
il
it
y
C
o
n
tr
o
l
i
n
En
c
ry
p
ted
a
n
d
C
o
m
p
re
ss
e
d
Do
m
a
in
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
I
n
fo
rm
a
ti
o
n
Fo
re
n
sic
s
a
n
d
S
e
c
u
rity
,
v
o
l.
1
5
,
p
p
.
2
5
5
6
-
2
5
6
9
,
F
e
b
.
2
0
2
0
,
d
o
i:
1
0
.
1
1
0
9
/T
IF
S
.
2
0
2
0
.
2
9
7
2
1
5
9
.
[6
]
A
.
Na
g
m
a
n
d
M
.
S
a
fy
,
“
A
R
o
b
u
st
Wate
rm
a
rk
in
g
Alg
o
rit
h
m
fo
r
M
e
d
ica
l
Im
a
g
e
s
,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
E
lec
trica
l
En
g
i
n
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
1
4
,
n
o
.
2
,
p
p
.
0
1
-
1
4
,
M
a
y
.
2
0
1
9
,
d
o
i:
1
0
.
1
1
5
9
1
/
ij
e
e
c
s.v
1
4
.
i
2
.
p
p
a
b
-
c
d
.
[7
]
F
.
Q
.
A
.
Al
-
Yo
u
s
u
f
a
n
d
R
.
Di
n
,
“
Re
v
iew
o
n
se
c
u
re
d
d
a
ta
c
a
p
a
b
il
i
t
ies
o
f
c
ry
p
t
o
g
ra
p
h
y
,
ste
g
a
n
o
g
ra
p
h
y
,
a
n
d
wa
term
a
rk
in
g
d
o
m
a
in
,
”
In
d
o
n
e
sia
n
J
o
u
rn
a
l
o
f
El
e
c
trica
l
En
g
in
e
e
rin
g
a
n
d
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
1
7
,
n
o
.
2
,
p
p
.
1
0
5
3
-
1
0
5
9
,
F
e
b
.
2
0
2
0
,
d
o
i:
1
0
.
1
1
5
9
1
/i
jee
c
s.v
1
7
.
i
2
.
p
p
1
0
5
3
-
1
0
5
9
.
[8
]
A
.
M
.
Ab
d
u
laz
e
e
z
,
D
.
M
.
Ha
jy
,
D
.
Q
.
Zee
b
a
re
e
,
a
n
d
D
.
A
.
Ze
b
a
ri
,
“
Ro
b
u
st
wa
term
a
rk
in
g
sc
h
e
m
e
b
a
se
d
LW
T
a
n
d
S
VD
u
sin
g
a
rti
f
icia
l
b
e
e
c
o
lo
n
y
o
p
ti
m
iza
ti
o
n
,
”
I
n
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
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
2
1
,
n
o
.
2
,
p
p
.
1
2
1
8
-
1
2
2
9
,
F
e
b
.
2
0
2
1
,
d
o
i:
1
0
.
1
1
5
9
1
/
ij
e
e
c
s.v
2
1
.
i
2
.
p
p
1
2
1
8
-
1
2
2
9
.
[9
]
S
.
G
u
ll
,
N
.
A.
L
o
a
n
,
S
.
A.
P
a
ra
h
,
J
.
A.
S
h
e
ik
h
,
a
n
d
G.
M.
Bh
a
t
,
“
An
e
fficie
n
t
wa
term
a
rk
in
g
tec
h
n
i
q
u
e
f
o
r
tam
p
e
r
d
e
tec
ti
o
n
a
n
d
l
o
c
a
li
z
a
ti
o
n
o
f
m
e
d
ica
l
ima
g
e
s
,
”
J
o
u
rn
a
l
o
f
Amb
ien
t
In
telli
g
e
n
c
e
a
n
d
Hu
m
a
n
ize
d
Co
m
p
u
ti
n
g
,
v
o
l.
1
1
,
p
p
.
1
7
9
9
-
1
8
0
8
,
De
c
.
2
0
1
8
,
d
o
i
:
1
0
.
1
0
0
7
/s1
2
6
5
2
-
0
1
8
-
1
1
5
8
-
8.
[1
0
]
S
.
N.
P
ra
jwa
las
imh
a
,
C
.
S
u
p
u
th
ra
,
a
n
d
C.
S
.
M
o
h
a
n
,
“
P
e
rfo
rm
a
n
c
e
a
n
a
ly
sis
o
f
DCT
a
n
d
su
c
c
e
ss
iv
e
d
iv
isi
o
n
b
a
se
d
d
ig
it
a
l
ima
g
e
wa
term
a
r
k
in
g
sc
h
e
m
e
,
”
In
d
o
n
e
sia
n
J
o
u
r
n
a
l
o
f
El
e
c
t
ric
a
l
En
g
in
e
e
rin
g
a
n
d
Co
m
p
u
ter
S
c
ien
c
e
,
v
o
l.
1
5
,
n
o
.
2
,
p
p
.
7
5
0
-
7
5
7
,
A
u
g
.
2
0
1
9
,
d
o
i
:
1
0
.
1
1
5
9
1
/
ij
e
e
c
s.v
1
5
.
i2
.
p
p
7
5
0
-
7
5
7
.
[1
1
]
A
.
Ba
m
a
traf,
R
.
Ib
ra
h
im,
a
n
d
M
.
N
.
B.
M
.
S
a
ll
e
h
,
“
Dig
it
a
l
Wate
rm
a
rk
in
g
Al
g
o
rit
h
m
Us
in
g
LS
B
,
”
2
0
1
0
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
C
o
mp
u
ter
A
p
p
li
c
a
ti
o
n
s
a
n
d
In
d
u
stria
l
E
lec
tro
n
ics
,
Ja
n
.
2
0
1
1
,
p
p
.
1
5
5
-
1
5
9
,
d
o
i:
1
0
.
1
1
0
9
/ICCAIE.
2
0
1
0
.
5
7
3
5
0
6
6
.
[1
2
]
C
.
C
.
Ch
a
n
g
,
P
.
Tsa
i,
a
n
d
C
.
C
.
Li
n
,
“
S
VD
-
b
a
se
d
d
i
g
it
a
l
ima
g
e
wa
term
a
rk
in
g
sc
h
e
m
e
,
”
Pa
tt
e
rn
Rec
o
g
n
it
i
o
n
L
e
tt
e
rs
,
v
o
l
.
2
6
,
p
p
.
1
5
7
7
-
1
5
8
6
,
J
u
l.
2
0
0
5
,
d
o
i:
1
0
.
1
0
1
6
/j
.
p
a
trec
.
2
0
0
5
.
0
1
.
0
0
4
.
[1
3
]
R.
Aa
rth
i,
V.
Ja
g
a
y
n
a
,
a
n
d
S
.
P
o
o
n
k
u
n
tran
,
“
M
o
d
ifi
e
d
LS
B
Wate
rm
a
rk
in
g
f
o
r
Im
a
g
e
Au
th
e
n
ti
c
a
ti
o
n
,
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Co
mp
u
ter
&
Co
mm
u
n
ica
ti
o
n
T
e
c
h
n
o
l
o
g
y
,
v
o
l.
6
,
p
p
.
5
-
8
,
Ju
n
.
2
0
1
5
,
d
o
i:
1
0
.
4
7
8
9
3
/IJCCT
.
2
0
1
5
.
1
2
6
4
.
[1
4
]
K
.
Ku
rih
a
ra
,
M
.
Kik
u
c
h
,
S
.
Im
a
izu
m
m
i,
S
.
S
h
i
o
ta,
a
n
d
H
.
Kiy
a
,
“
An
En
c
ry
p
ti
o
n
t
h
e
n
Co
m
p
re
ss
io
n
S
y
ste
m
fo
r
JPE
G
/M
o
ti
o
n
JP
EG
S
tan
d
a
rd
,
”
IEI
CE
T
ra
n
sa
c
ti
o
n
s
o
n
F
u
n
d
a
me
n
ta
ls
o
f
El
e
c
tro
n
ics
,
Co
mm
u
n
ica
ti
o
n
s
a
n
d
Co
mp
u
ter
S
c
ien
c
e
s
,
v
o
l.
E
9
8
.
A,
n
o
.
1
1
,
p
p
.
2
2
3
8
-
2
2
4
5
,
N
o
v
.
2
0
1
5
,
d
o
i:
1
0
.
1
5
8
7
/t
ra
n
sf
u
n
.
E9
8
.
A.2
2
3
8
.
[1
5
]
J
.
M
.
G
a
rc
ia,
B
.
P
.
G
.
S
a
l
g
a
d
o
,
V
.
P
o
n
o
m
a
ry
o
v
,
R.
R.
Re
y
e
s,
S
.
S
a
d
o
v
n
y
c
h
i
y
,
a
n
d
C.
C.
Ra
m
o
s,
“
An
e
ffe
c
ti
v
e
fra
g
il
e
wa
term
a
rk
in
g
sc
h
e
m
e
fo
r
c
o
lo
r
ima
g
e
tam
p
e
rin
g
d
e
tec
ti
o
n
a
n
d
se
lf
-
re
c
o
v
e
ry
,
”
S
ig
n
a
l
Pr
o
c
e
ss
in
g
:
Ima
g
e
Co
mm
u
n
ica
ti
o
n
,
v
o
l
.
8
1
,
2
0
2
0
,
d
o
i:
1
0
.
1
0
1
6
/
j.
ima
g
e
.
2
0
1
9
.
1
1
5
7
2
5
.
[
1
6
]
O
.
E
v
s
u
t
i
n
,
A
.
M
e
l
m
a
n
,
a
n
d
R
.
M
e
s
h
c
h
e
r
y
a
k
o
v
,
“
D
i
g
i
t
a
l
S
t
e
g
a
n
o
g
r
a
p
h
y
a
n
d
W
a
t
e
r
m
a
r
k
i
n
g
f
o
r
D
i
g
i
t
a
l
I
m
a
g
e
s
:
A
R
e
v
i
e
w
o
f
C
u
r
r
e
n
t
R
e
s
e
a
r
c
h
D
i
r
e
c
t
i
o
n
s
,
”
I
E
E
E
A
c
c
e
s
s
,
v
o
l
.
8
,
p
p
.
1
6
6
5
8
9
-
1
6
6
6
1
1
,
2
0
2
0
,
d
o
i
:
1
0
.
1
1
0
9
/
A
C
C
E
S
S
.
2
0
2
0
.
3
0
2
2
7
7
9
.
[1
7
]
R
.
Liu
a
n
d
T
.
Tan
,
”
An
S
VD
-
Ba
se
d
Wate
rm
a
rk
in
g
S
c
h
e
m
e
fo
r
P
ro
tec
ti
n
g
Ri
g
h
tf
u
l
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
M
u
lt
ime
d
ia
,
v
o
l.
4
,
n
o
,
p
p
.
1
2
1
-
12
8
,
M
a
r.
2
0
0
2
,
d
o
i:
1
0
.
1
1
0
9
/
6
0
4
6
.
9
8
5
5
6
0
.
[1
8
]
J
.
F
.
Ya
n
g
a
n
d
C
.
L.
L
u
,
“
Co
m
b
i
n
e
d
tec
h
n
i
q
u
e
s o
f
sin
g
u
lar v
a
lu
e
d
e
c
o
m
p
o
siti
o
n
a
n
d
v
e
c
to
r
q
u
a
n
ti
z
a
ti
o
n
f
o
r
ima
g
e
c
o
d
in
g
,
”
I
EE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Im
a
g
e
Pro
c
e
ss
in
g
,
v
o
l
.
4
,
n
o
.
8
,
p
p
.
1
1
4
1
-
1
1
4
6
,
A
u
g
.
1
9
9
5
,
d
o
i:
1
0
.
1
1
0
9
/8
3
.
4
0
3
4
1
9
.
[1
9
]
X
.
To
n
g
e
t
a
l
.
,
“
Im
a
g
e
Re
g
ist
ra
ti
o
n
W
it
h
F
o
u
rier
-
Ba
se
d
Im
a
g
e
Co
rre
latio
n
:
A
Co
m
p
re
h
e
n
si
v
e
Re
v
iew
o
f
De
v
e
lo
p
m
e
n
ts
a
n
d
A
p
p
li
c
a
ti
o
n
s
,
”
IEE
E
J
o
u
rn
a
l
o
f
S
e
lec
ted
T
o
p
ics
in
Ap
p
li
e
d
E
a
rth
Ob
se
rv
a
ti
o
n
s
a
n
d
Rem
o
te
S
e
n
sin
g
,
v
o
l.
1
2
,
n
o
.
1
0
,
p
p
.
4
0
6
2
-
4
0
8
1
,
Oc
t.
2
0
1
9
,
d
o
i
:
1
0
.
1
1
0
9
/JS
TARS
.
2
0
1
9
.
2
9
3
7
6
9
0
.
[2
0
]
A
.
Da
p
e
n
a
a
n
d
S
.
Ah
a
lt
,
“
A
Hy
b
rid
DCT
-
S
VD
Im
a
g
e
-
Co
d
in
g
Alg
o
rit
h
m
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Circ
u
it
s
a
n
d
S
y
ste
ms
fo
r V
id
e
o
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
2
,
n
o
.
2
,
p
p
.
1
1
4
-
1
2
1
,
F
e
b
.
2
0
0
2
,
d
o
i
:
1
0
.
1
1
0
9
/7
6
.
9
8
8
6
5
8
.
[2
1
]
F
.
Hu
a
n
g
,
X
.
Qu
,
H
.
J
.
Kim
,
a
n
d
J
.
Hu
a
n
g
,
“
Re
v
e
rsib
le
Da
ta
Hid
in
g
in
JPE
G
Im
a
g
e
s
,
”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Circ
u
it
s
a
n
d
S
y
ste
ms
fo
r
Vi
d
e
o
T
e
c
h
n
o
lo
g
y
,
v
o
l
.
2
6
,
n
o
.
9
,
p
p
.
1
6
1
0
-
1
6
2
1
,
S
e
p
.
2
0
1
6
,
d
o
i:
1
0
.
1
1
0
9
/T
CS
VT
.
2
0
1
5
.
2
4
7
3
2
3
5
.
[2
2
]
R
.
K
.
S
i
n
g
h
,
D
.
K
.
S
h
a
w,
a
n
d
M
.
J
.
Ala
m
,
“
E
x
p
e
rime
n
tal
S
t
u
d
ies
o
f
LS
B
Wate
rm
a
rk
in
g
wit
h
Diffe
re
n
t
No
ise
,
”
Pro
c
e
d
ia
C
o
mp
u
ter
S
c
ien
c
e
,
v
o
l.
5
4
,
p
p
.
6
1
2
-
6
2
0
,
2
0
1
5
,
d
o
i:
1
0
.
1
0
1
6
/j
.
p
r
o
c
s.2
0
1
5
.
0
6
.
0
7
1
.
[2
3
]
G
.
J
.
Lee
,
E
.
J
.
Yo
o
n
,
a
n
d
K
.
Y
.
Yo
o
,
“
A
n
e
w
LS
B
b
a
se
d
Dig
it
a
l
Wate
rm
a
rk
in
g
S
c
h
e
m
e
with
Ra
n
d
o
m
M
a
p
p
i
n
g
F
u
n
c
ti
o
n
,
”
2
0
0
8
In
ter
n
a
ti
o
n
a
l
S
y
mp
o
si
u
m
o
n
Ub
i
q
u
it
o
u
s
M
u
l
ti
me
d
ia
C
o
mp
u
ti
n
g
,
Oc
t.
2
0
0
8
,
p
p
.
1
3
0
-
1
3
4
,
d
o
i:
1
0
.
1
1
0
9
/UM
C.
2
0
0
8
.
3
3
.
[2
4
]
T
.
Rich
ter,
“
S
S
IM
a
s
G
lo
b
a
l
Qu
a
l
it
y
M
e
tri
c
:
A
Diffe
re
n
ti
a
l
G
e
o
m
e
try
Vie
w
,
”
2
0
1
1
T
h
ir
d
In
ter
n
a
ti
o
n
a
l
W
o
rk
sh
o
p
o
n
Q
u
a
li
ty o
f
M
u
lt
ime
d
i
a
Exp
e
rie
n
c
e
,
No
v
.
2
0
1
1
,
p
p
.
1
8
9
-
1
9
4
,
d
o
i
:
1
0
.
1
1
0
9
/Qo
M
EX
.
2
0
1
1
.
6
0
6
5
7
0
1
.
[2
5
]
A
.
Ho
ré
a
n
d
D
.
Zi
o
u
,
“
Im
a
g
e
q
u
a
li
ty
m
e
tri
c
s:
P
S
NR
v
s.
S
S
IM
,
”
2
0
1
0
2
0
th
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
P
a
tt
e
rn
Rec
o
g
n
it
io
n
,
Oc
t.
2
0
1
0
,
p
p
.
2
3
6
6
-
2
3
6
9
,
d
o
i:
1
0
.
1
1
0
9
/IC
P
R.
2
0
1
0
.
5
7
9
.
Evaluation Warning : The document was created with Spire.PDF for Python.