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5
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E
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to
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id
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tialit
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[
6
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.
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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I
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N:
2088
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8708
A
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t
h
e
s
te
g
o
-
i
m
a
g
e,
b
u
t
in
s
tead
,
th
e
q
u
alit
y
r
elate
d
to
th
e
o
r
ig
in
al
co
v
er
i
m
a
g
e,
o
r
in
o
th
er
w
o
r
d
s
,
th
e
d
i
f
f
ic
u
lt
y
to
d
if
f
er
e
n
tiate
a
m
o
n
g
th
e
t
w
o
i
m
a
g
es (
s
te
g
o
,
an
d
co
v
er
)
.
I
n
th
is
p
ap
er
,
a
n
e
w
tech
n
iq
u
e
ai
m
s
to
m
i
n
i
m
ize
th
e
n
u
m
b
er
o
f
m
o
d
if
icatio
n
s
in
t
h
e
ca
r
r
ier
im
a
g
e
d
ata
w
h
e
n
e
m
b
ed
d
in
g
co
n
f
id
en
tial
in
f
o
r
m
a
tio
n
h
a
s
b
ee
n
s
u
g
g
e
s
ted
.
C
o
v
er
i
m
a
g
e
is
f
i
r
s
t
p
ar
tit
io
n
ed
in
to
s
m
al
ler
s
ized
b
lo
ck
s
,
a
n
d
t
h
e
s
i
m
ilar
it
y
b
et
w
ee
n
ea
c
h
i
n
d
i
v
id
u
al
b
lo
c
k
b
its
a
n
d
t
h
eir
co
r
r
esp
o
n
d
in
g
b
it
s
o
f
th
e
m
ess
a
g
e
w
a
n
ted
to
b
e
co
n
ce
aled
is
tak
e
n
in
to
co
n
s
id
er
at
io
n
w
h
e
n
co
d
in
g
th
e
s
ec
r
et
m
ess
a
g
e
in
to
a
s
teg
o
-
i
m
a
g
e.
Me
s
s
a
g
e
b
its
ar
e
e
n
c
o
d
e
d
in
o
n
e
d
ir
ec
tio
n
w
h
e
n
th
er
e
is
a
d
o
m
i
n
a
n
t
s
i
m
ilar
i
t
y
,
an
d
en
co
d
ed
in
th
e
r
ev
er
s
e
d
ir
ec
tio
n
w
h
e
n
t
h
e
d
is
s
i
m
ilar
it
y
i
s
d
o
m
i
n
an
t
b
et
w
ee
n
t
h
e
m
es
s
ag
e
an
d
t
h
e
c
o
r
r
esp
o
n
d
in
g
co
v
er
b
its
.
T
h
e
L
SB
o
f
t
h
e
co
v
er
i
m
ag
e
is
to
b
e
a
m
e
n
d
ed
ac
co
r
d
in
g
to
th
is
cr
i
ter
io
n
,
i
n
o
r
d
er
to
ac
co
m
m
o
d
ate
th
e
s
ec
r
et
m
ess
a
g
e.
T
h
is
w
a
y
t
h
e
n
u
m
b
er
o
f
m
o
d
i
f
icatio
n
s
in
th
e
b
its
th
e
ca
r
r
ier
’
s
L
SB
w
ill
b
e
r
ed
u
ce
d
r
esu
lti
n
g
in
a
n
en
h
an
ce
d
v
is
i
b
le
q
u
alit
y
o
f
t
h
e
s
te
g
o
-
i
m
a
g
e,
an
d
h
en
ce
en
h
a
n
ce
d
i
m
p
er
ce
p
tib
ilit
y
.
I
n
t
h
is
p
ap
er
,
s
ec
tio
n
I
I
d
is
cu
s
s
es
t
h
e
d
if
f
er
en
t
s
tr
ate
g
ies
u
s
ed
f
o
r
i
m
a
g
e
s
teg
a
n
o
g
r
ap
h
y
.
I
n
a
d
d
itio
n
,
s
ec
tio
n
I
I
I
ex
p
lain
s
t
h
e
co
n
v
e
n
tio
n
al
L
S
B
s
teg
a
n
o
g
r
ap
h
y
s
y
s
te
m
.
Sect
io
n
I
V
o
n
t
h
e
o
t
h
er
h
a
n
d
,
s
h
o
w
s
t
h
e
ex
p
er
i
m
en
tal
r
esu
lt
s
o
f
o
u
r
p
r
o
p
o
s
ed
alg
o
r
ith
m
,
an
d
co
m
p
ar
e
w
it
h
th
e
o
th
er
ex
is
t
en
t
al
g
o
r
ith
m
s
in
t
er
m
s
o
f
t
h
e
Me
a
n
Sq
u
ar
e
E
r
r
o
r
,
MSE
,
an
d
th
e
Stru
ctu
r
al
Si
m
i
lar
it
y
,
S
SIM
,
in
d
ex
.
Fi
n
all
y
,
s
ec
tio
n
I
V
co
n
cl
u
d
es th
is
p
ap
er
.
2.
I
M
AG
E
ST
E
G
ANO
G
RAP
H
Y
I
t
is
v
er
y
f
a
m
iliar
to
h
id
e
in
f
o
r
m
atio
n
w
ith
in
an
i
m
a
g
e
as
a
co
n
s
eq
u
en
ce
to
th
e
r
elati
v
el
y
h
i
g
h
s
to
r
ag
e
ca
p
ac
it
y
as
w
ell
as
s
a
tis
f
y
i
n
g
i
m
p
er
ce
p
tib
ilit
y
i
t
o
f
f
er
s
d
u
e
to
th
e
lar
g
e
n
u
m
b
er
o
f
r
ed
u
n
d
an
t
b
its
it
co
n
tain
s
[
7
]
.
I
m
ag
es
ar
e
d
ea
lt
w
it
h
in
co
m
p
u
ter
as
f
i
x
ed
s
iz
e
m
atr
ices
o
f
p
ix
el
s
.
T
h
ese
p
ix
els
ar
e
r
ep
r
esen
ted
in
m
an
y
d
i
f
f
er
en
t
w
a
y
s
d
ep
en
d
i
n
g
o
n
t
h
e
t
y
p
e
i
m
a
g
e
co
d
in
g
u
s
ed
.
I
n
g
r
a
y
-
s
ca
led
i
m
a
g
e
t
y
p
e,
ea
ch
p
i
x
el
is
ex
p
r
ess
ed
b
y
a
s
in
g
le
8
-
b
it
v
a
lu
e
w
h
ic
h
r
ep
r
esen
ts
th
e
d
e
g
r
ee
o
f
th
e
g
r
a
y
s
ca
le
t
h
is
p
i
x
el
h
as,
g
r
ad
ed
f
r
o
m
0
to
2
5
5
[
8
]
.
I
n
co
n
tr
ast,
in
d
e
x
ed
i
m
a
g
es,
u
s
e
t
h
e
p
ix
el
’
s
v
a
lu
e
to
r
ef
er
to
a
s
ep
ar
ate
s
tan
d
-
alo
n
e
i
n
d
ex
,
w
h
ich
i
n
tu
r
n
d
ef
i
n
e
s
th
e
h
u
e
o
f
th
is
p
ix
el
ac
cu
r
atel
y
.
B
lack
an
d
w
h
it
e
i
m
ag
e
s
u
s
e
t
h
e
v
al
u
e
o
f
0
to
r
ep
r
esen
t
th
e
b
lac
k
co
lo
r
,
an
d
1
t
o
r
ep
r
esen
t
w
h
it
e,
w
h
er
e
n
o
b
lack
n
e
s
s
g
r
ad
in
g
is
o
f
f
er
ed
[
8
]
.
On
th
e
o
th
er
h
an
d
,
R
GB
i
m
a
g
e
u
tili
ze
s
th
r
ee
8
-
b
its
n
u
m
b
er
s
t
o
d
ef
in
e
th
e
q
u
a
n
tit
y
o
f
r
ed
n
e
s
s
,
g
r
ee
n
n
e
s
s
,
an
d
b
lu
e
n
ess
o
f
th
e
co
r
r
esp
o
n
d
in
g
p
ix
el
[
8
]
.
Sin
ce
t
h
e
b
an
d
w
id
t
h
o
f
co
m
m
u
n
icat
io
n
n
et
w
o
r
k
s
is
li
m
i
t
ed
d
u
e
t
o
th
e
v
a
s
t
n
u
m
b
er
o
f
u
s
er
s
,
a
n
d
th
e
n
u
m
er
o
u
s
b
a
n
d
w
id
th
ea
ti
n
g
ap
p
licat
io
n
s
t
h
at
ar
e
u
s
ed
o
v
er
th
ese
n
et
w
o
r
k
s
,
th
i
s
m
ak
es
u
p
lo
ad
in
g
a
n
d
d
o
w
n
lo
ad
i
n
g
b
i
g
s
ized
i
m
ag
e
s
an
i
n
e
f
f
icie
n
t
w
a
y
[
9
]
.
A
lter
n
ativ
el
y
,
i
m
a
g
es
ar
e
u
s
ed
to
b
e
co
m
p
r
es
s
ed
b
ef
o
r
e
b
ein
g
f
o
r
w
ar
d
ed
o
n
th
e
n
et
w
o
r
k
’
s
lin
k
s
.
Dif
f
er
en
t
ap
p
r
o
ac
h
es
w
ith
d
i
f
f
er
en
t
p
er
f
o
r
m
a
n
ce
s
ex
i
s
t
in
t
h
i
s
ar
ea
.
T
h
ese
ap
p
r
o
ac
h
es
ca
n
b
e
r
o
u
g
h
l
y
cla
s
s
i
f
ied
i
n
to
t
w
o
m
ain
t
y
p
e
s
,
lo
s
s
y
a
n
d
lo
s
s
less
co
m
p
r
ess
io
n
tech
n
iq
u
es.
I
n
lo
s
s
y
s
y
s
te
m
,
u
n
n
ec
es
s
ar
y
i
n
f
o
r
m
atio
n
o
f
i
m
a
g
e
i
s
r
e
m
o
v
ed
to
ac
h
i
ev
e
a
s
u
b
s
ta
n
tial
d
i
f
f
er
en
ce
i
n
th
e
i
m
a
g
e
s
ize,
w
h
er
ea
s
lo
s
s
less
tec
h
n
iq
u
es
u
s
ed
s
o
m
e
s
tatis
tical
s
tr
ate
g
ie
s
to
r
ed
u
ce
th
e
n
u
m
b
er
o
f
r
ed
u
n
d
an
cie
s
in
i
m
a
g
e,
an
d
h
e
n
ce
r
ed
u
ce
th
e
o
r
ig
i
n
al
i
m
a
g
e
s
ize
[
1
0
]
.
On
e
o
f
t
h
e
m
o
s
t
co
m
m
o
n
co
m
p
r
e
s
s
io
n
tec
h
n
o
lo
g
ies
u
s
ed
is
t
h
e
J
P
E
G
(
J
o
in
t
P
h
o
to
g
r
ap
h
ic
E
x
p
er
ts
Gr
o
u
p
)
im
a
g
e
co
d
in
g
.
T
h
e
latest
u
s
e
s
a
lo
s
s
y
co
m
p
r
ess
io
n
s
ch
e
m
e,
w
h
er
e
t
h
e
i
m
a
g
e
i
s
tr
an
s
f
o
r
m
ed
f
r
o
m
i
ts
s
p
ec
ial
co
o
r
d
in
ates
in
to
f
r
eq
u
en
c
y
d
o
m
a
in
co
o
r
d
in
ates.
T
h
e
m
aj
o
r
id
ea
is
s
tan
d
in
g
b
e
y
o
n
d
th
e
i
n
ab
ilit
y
o
f
h
u
m
a
n
e
y
es
to
r
ec
o
g
n
ize
ch
a
n
g
e
s
o
f
i
m
ag
e
s
i
n
h
i
g
h
f
r
eq
u
en
c
y
s
p
ec
tr
u
m
[
1
1
]
.
Dis
cr
ete
C
o
s
i
n
e
T
r
an
s
f
o
r
m
(
DC
T
)
w
h
ic
h
is
a
m
o
d
i
f
ied
v
e
r
s
io
n
o
f
Di
s
cr
ete
Fas
t
Fo
u
r
ier
T
r
an
s
f
o
r
m
(
DFFT
)
is
u
s
ed
to
r
ep
r
esen
t
th
e
i
m
a
g
e
in
f
r
eq
u
e
n
c
y
d
o
m
ain
.
On
l
y
th
e
s
m
a
ll
p
o
r
tio
n
o
f
i
m
ag
e
in
f
o
r
m
atio
n
w
h
ich
is
lo
ca
ted
at
lo
w
f
r
eq
u
e
n
c
y
s
p
ac
e
i
s
k
ep
t
s
u
r
v
i
v
ed
,
w
h
er
ea
s
all
o
t
h
er
d
ata
is
o
m
itted
.
DW
T
(
Dis
cr
ete
W
av
elet
T
r
an
s
f
o
r
m
)
is
a
ls
o
s
o
m
et
i
m
e
s
u
s
ed
to
co
m
p
r
ess
i
m
a
g
e
f
iles
[
1
2
]
.
I
n
i
m
a
g
e
s
t
e
g
a
n
o
g
r
ap
h
y
,
a
s
t
h
e
n
a
m
e
i
m
p
lies
,
t
h
e
m
ed
i
u
m
to
h
id
e
s
ec
r
et
in
f
o
r
m
atio
n
b
e
h
in
d
i
s
an
i
m
a
g
e,
w
h
er
e
t
h
is
tech
n
iq
u
e
ex
p
lo
its
t
h
e
li
m
ited
ca
p
ab
il
it
y
o
f
h
u
m
a
n
’
s
e
y
e
to
p
er
ce
p
t
s
o
m
e
k
i
n
d
s
o
f
ad
j
u
s
t
m
e
n
ts
i
n
th
e
co
v
er
i
m
a
g
e.
Ma
n
y
a
s
p
ec
ts
o
f
h
u
m
an
e
y
e’
s
li
m
itatio
n
s
w
er
e
in
v
est
ed
to
ac
c
o
m
m
o
d
ate
th
e
s
ec
r
ete
m
e
s
s
a
g
e
w
it
h
in
t
h
e
ca
r
r
ier
im
ag
e
w
i
th
o
u
t
b
ein
g
n
o
ticed
b
y
u
n
tar
g
eted
w
atc
h
er
s
.
No
te
th
at
lo
s
s
y
i
m
a
g
e
co
m
p
r
ess
io
n
tec
h
n
iq
u
e
s
ar
e
n
o
t
s
u
itab
le
f
o
r
s
o
m
e
t
y
p
es
o
f
s
teg
a
n
o
g
r
ap
h
y
s
i
n
ce
th
e
i
m
p
o
r
tan
t
m
e
s
s
a
g
e
b
its
ca
n
b
e
m
is
s
ed
as
v
icti
m
o
f
ap
p
l
y
i
n
g
t
h
e
co
m
p
r
e
s
s
io
n
m
et
h
o
d
[
1
3
]
.
A
cc
o
r
d
in
g
to
th
e
w
a
y
o
f
h
id
i
n
g
th
e
p
r
iv
ate
d
ata
w
it
h
in
t
h
e
co
v
er
f
ile,
i
m
a
g
e
s
te
g
a
n
o
g
r
ap
h
y
c
an
b
e
class
i
f
ied
in
to
th
r
ee
m
aj
o
r
k
in
d
s
.
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.
9
,
No
.
6
,
Dec
em
b
er
201
9
:
5
2
8
6
-
5
2
9
4
5288
a.
Data
I
n
s
er
tio
n
Stra
teg
y
T
h
is
k
i
n
d
d
ep
en
d
s
o
n
i
n
s
er
ti
n
g
th
e
d
ata
o
f
th
e
s
ec
r
et
m
e
s
s
a
g
e
i
n
p
l
ac
es
o
f
t
h
e
ca
r
r
ier
i
m
a
g
e
w
h
er
e
th
e
w
atc
h
er
w
il
l
n
o
t
p
er
ce
i
v
e
.
Of
co
u
r
s
e,
t
h
is
r
ed
u
n
d
an
t
d
ata
ad
d
itio
n
w
ill
b
e
ac
co
m
p
an
ied
b
y
i
m
a
g
e
s
ize
e
n
lar
g
e
m
e
n
t
w
h
ic
h
m
a
y
b
e
co
n
s
id
er
ed
as
a
clea
r
d
r
a
wb
ac
k
o
f
th
e
s
y
s
te
m
.
Ho
w
ev
er
,
th
i
s
m
et
h
o
d
o
f
s
teg
a
n
o
g
r
ap
h
y
p
o
s
s
ess
e
s
g
o
o
d
d
eg
r
ee
o
f
i
m
p
er
ce
p
tib
ilit
y
s
i
n
ce
p
r
iv
ate
d
ata
ar
e
u
s
ed
to
b
e
e
m
b
ed
d
ed
in
lo
ca
tio
n
s
th
at
ar
e
u
s
u
all
y
i
g
n
o
r
ed
b
y
th
e
ap
p
licatio
n
th
at
d
is
p
la
y
s
t
h
e
i
m
a
g
e,
s
u
c
h
as
in
th
e
h
ea
d
er
o
r
tr
ailer
o
f
th
e
i
m
ag
e
’
s
f
ile
[
1
4
]
.
b.
Data
R
ep
lace
m
e
n
t S
tr
ateg
y
I
n
co
n
tr
ast
to
th
e
d
ata
i
n
s
er
t
io
n
tech
n
iq
u
e,
t
h
is
m
et
h
o
d
d
o
es
n
o
t
m
a
k
e
an
y
ch
a
n
g
e
to
th
e
s
ize
o
f
th
e
ca
r
r
ier
i
m
ag
e
f
ile,
s
i
n
ce
it
d
o
es
n
o
t
in
s
er
t
an
y
m
o
r
e
b
its
.
I
n
s
tead
,
th
i
s
tech
n
iq
u
e
r
ep
lace
s
s
o
m
e
b
its
o
f
th
e
o
r
ig
in
al
co
v
er
i
m
a
g
e
w
h
ic
h
h
av
e
m
in
o
r
e
f
f
ec
ts
o
n
th
e
a
p
p
ea
r
an
ce
o
f
t
h
e
r
es
u
lt
in
g
i
m
a
g
e.
T
h
e
s
p
ac
e
th
at
is
a
v
ailab
le
f
o
r
e
m
b
ed
d
in
g
th
e
p
r
iv
ate
d
ata
is
to
tall
y
g
o
v
er
n
ed
b
y
th
e
n
u
m
b
er
o
f
in
s
i
g
n
i
f
ican
t
b
its
o
f
th
e
co
v
er
i
m
a
g
e.
T
h
e
i
m
p
er
ce
p
tib
ilit
y
m
ea
s
u
r
e
is
th
i
s
m
et
h
o
d
d
e
p
en
d
s
o
n
th
e
d
eg
r
e
e
o
f
s
ig
n
if
ican
ce
o
f
th
e
r
ep
lace
d
b
its
,
an
d
th
e
d
eg
r
ee
o
f
s
i
m
i
lar
it
y
to
t
h
e
o
r
ig
i
n
al
i
m
a
g
e,
th
e
m
o
r
e
s
i
m
ilar
th
e
s
teg
o
-
i
m
ag
e
o
b
tain
ed
,
th
e
m
o
r
e
th
e
p
er
f
o
r
m
an
ce
ac
h
ie
v
ed
[
1
4
]
.
c.
C
o
v
er
I
m
a
g
e
Gen
er
atio
n
Stra
t
eg
y
I
n
co
n
tr
ast
to
th
e
o
t
h
er
s
tr
ate
g
ies,
th
i
s
o
n
e
u
s
es
a
o
n
e
-
w
a
y
a
lg
o
r
ith
m
to
co
n
s
tr
u
ct
a
u
n
iq
u
e
co
v
er
i
m
ag
e
co
r
r
esp
o
n
d
in
g
to
ea
ch
p
r
iv
at
e
m
ess
a
g
e.
T
h
is
w
a
y
s
tr
en
g
t
h
en
s
th
e
s
y
s
te
m
a
g
ai
n
s
t
m
al
icio
u
s
attac
k
s
w
h
ic
h
u
t
ilizes
a
co
m
p
ar
i
s
o
n
b
et
w
ee
n
,
th
e
s
teg
o
a
n
d
co
v
e
r
i
m
ag
e
s
to
d
is
co
v
er
t
h
e
h
id
d
en
m
e
s
s
a
g
e.
T
h
e
m
a
j
o
r
p
r
o
b
lem
w
i
th
t
h
i
s
m
et
h
o
d
is
t
h
e
r
an
d
o
m
b
eh
a
v
io
r
o
f
t
h
is
a
lg
o
r
it
h
m
,
w
h
er
e
th
e
g
en
er
ated
i
m
a
g
e
co
n
s
i
s
ts
o
f
r
an
d
o
m
s
h
a
p
es a
n
d
co
lo
r
s
,
w
h
ic
h
m
a
y
b
e
s
u
s
p
ec
ted
b
y
t
h
e
en
d
u
s
er
s
[
1
4
]
.
3.
I
M
AG
E
ST
E
G
ANA
L
Y
SI
S
T
h
e
ter
m
s
teg
a
n
a
lysi
s
r
ef
er
s
to
tech
n
iq
u
e
s
u
s
ed
to
r
e
v
ea
l
th
e
h
id
d
en
in
f
o
r
m
a
tio
n
e
m
b
ed
d
ed
in
th
e
co
v
er
f
ile
[
1
5
,
1
6
]
.
Ma
n
y
al
g
o
r
ith
m
s
w
er
e
i
n
tr
o
d
u
ce
d
f
o
r
th
i
s
p
u
r
p
o
s
e.
T
h
e
s
teg
a
n
o
g
r
ap
h
y
s
y
s
te
m
is
co
n
s
id
er
ed
b
r
o
k
en
as
s
o
o
n
as
t
h
e
h
id
d
en
d
ata
is
e
x
tr
ac
ted
f
r
o
m
t
h
e
co
v
er
f
ile,
e
v
en
th
o
u
g
h
s
u
c
h
d
ata
h
a
v
e
n
o
t
b
ee
n
d
ec
o
d
ed
o
r
d
ec
ip
h
er
ed
t
o
its
o
r
ig
i
n
al
s
ec
r
et
m
es
s
ag
e.
I
n
f
ac
t
an
y
c
h
a
n
g
e
th
a
t
is
m
a
d
e
to
th
e
co
v
er
f
il
e
h
as
it
s
o
w
n
e
f
f
ec
t
o
n
t
h
e
ch
ar
ac
ter
is
tics
o
f
th
e
co
v
er
i
m
a
g
e;
th
is
r
ea
lit
y
o
p
en
s
th
e
d
o
o
r
to
th
e
s
te
g
r
an
o
g
r
ap
h
ic
ef
f
o
r
t
s
.
T
h
e
f
o
llo
w
in
g
th
r
ee
m
ai
n
t
y
p
e
s
o
f
i
m
a
g
e
s
te
g
an
al
y
s
i
s
tec
h
n
iq
u
e
s
ca
n
b
e
d
is
tin
g
u
i
s
h
ed
.
(
i)
P
ass
i
v
e
s
teg
a
n
al
y
s
i
s
attac
k
i
n
g
tec
h
n
iq
u
e:
T
h
e
ai
m
o
f
t
h
is
tech
n
iq
u
e
is
to
d
is
co
v
er
a
n
d
r
ea
d
th
e
p
r
iv
ate
m
es
s
ag
e
s
to
r
ed
in
th
e
ca
r
r
ier
i
m
ag
e
w
it
h
o
u
t
a
n
y
tr
en
d
to
m
o
d
if
y
t
h
e
s
te
g
o
im
ag
e
d
ata.
T
h
er
e
f
o
r
e
th
is
m
et
h
o
d
k
ee
p
s
th
e
s
etg
o
-
f
ile
in
tact
[
1
7
]
.
(
ii)
A
ctiv
e
att
ac
k
s
:
T
h
is
attac
k
ch
an
g
e
s
th
e
co
n
ten
t
o
f
t
h
e
s
te
g
o
-
i
m
a
g
e
b
y
ad
d
in
g
s
o
m
e
n
o
is
e
to
th
e
i
m
ag
e
i
n
o
r
d
er
to
p
r
ev
en
t
an
y
p
r
o
b
ab
le
s
ec
r
et
in
f
o
r
m
atio
n
f
r
o
m
b
ein
g
co
n
v
e
y
ed
as
a
p
r
ec
au
tio
n
ar
y
p
r
o
ce
d
u
r
e
ev
en
if
t
h
e
tr
a
n
s
m
it
te
d
i
m
a
g
e
w
as
o
u
t
o
f
s
u
s
p
icio
n
[
1
8
]
.
(
iii)
Ma
licio
u
s
a
ttack
in
g
tec
h
n
iq
u
e:
I
n
th
i
s
tech
n
iq
u
e,
t
h
e
a
ttack
er
n
o
t
o
n
l
y
h
as
th
e
ab
ilit
y
to
a
m
e
n
d
t
h
e
s
teg
o
-
i
m
ag
e,
b
u
t
f
u
r
th
er
t
h
e
y
p
lay
s
a
r
o
le
o
f
o
n
e
o
n
th
e
au
t
h
o
r
ized
co
m
m
u
n
ic
atin
g
p
ar
ties
b
y
r
ep
lacin
g
th
e
o
r
ig
in
al
s
te
g
o
-
i
m
a
g
e
b
y
a
f
ak
e
o
n
e
to
co
n
v
e
y
f
ab
r
icate
d
th
e
in
f
o
r
m
a
tio
n
t
h
e
y
w
an
t to
th
e
en
d
u
s
er
s
[
1
8
].
4.
CO
NVEN
T
I
O
NA
L
L
SB
ST
E
G
ANO
RARH
Y
M
E
T
H
O
D
E
ac
h
p
i
x
el
i
n
a
g
r
a
y
s
ca
led
i
m
ag
e
r
ep
r
esen
ts
th
e
d
ar
k
n
e
s
s
o
f
th
at
p
o
in
t
o
f
th
e
i
m
a
g
e
w
h
er
e
th
i
s
p
i
x
el
is
lo
ca
ted
.
T
h
e
v
a
lu
e
o
f
t
h
i
s
p
ix
el
r
an
g
e
s
f
r
o
m
0
to
2
5
5
t
o
in
ter
p
r
et
2
5
6
d
eg
r
ee
s
o
f
d
ar
k
n
e
s
s
.
T
h
e
v
al
u
e
0
co
r
r
esp
o
n
d
s
to
a
p
u
r
e
b
lack
co
lo
r
,
an
d
th
e
a
m
o
u
n
t
o
f
p
i
x
el
’
s
w
h
i
ten
e
s
s
i
n
cr
ea
s
es
w
i
th
th
e
in
cr
ea
s
e
t
h
is
v
al
u
e,
w
h
er
ea
s
th
e
v
alu
e
2
5
5
co
r
r
esp
o
n
d
s
to
a
p
u
r
e
w
h
i
te
co
lo
r
.
T
h
ese
2
5
6
lev
els
o
f
w
h
i
ten
e
s
s
ar
e
r
ep
r
esen
ted
b
y
an
8
-
b
it
n
u
m
b
er
.
I
t
is
clea
r
th
at
c
h
an
g
es
to
t
h
e
v
er
y
la
s
t
b
it
(
L
S
B
)
d
o
n
o
t
m
a
k
e
a
s
i
g
n
i
f
ica
n
t
c
h
an
g
e
i
n
th
e
v
a
lu
e
o
f
t
h
e
n
u
m
b
er
,
a
n
d
h
en
ce
i
n
a
m
o
u
n
t
o
f
d
ar
k
n
e
s
s
o
f
th
e
p
i
x
el
co
r
r
esp
o
n
d
in
g
to
t
h
at
n
u
m
b
er
.
Fo
r
i
n
s
ta
n
ce
,
if
o
n
e
ch
a
n
g
es
th
e
L
SB
o
f
a
p
ix
el
f
r
o
m
1
0
1
0
0
0
0
1
w
h
ic
h
r
ea
d
s
1
6
1
in
d
ec
i
m
a
l
to
1
0
1
0
0
0
0
0
w
h
ic
h
r
ea
d
s
1
6
0
,
th
e
v
al
u
e
o
f
d
ar
k
n
ess
d
o
es
n
o
t
in
cr
ea
s
e
th
a
t
m
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ca
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s
.
RE
F
E
R
E
NC
E
S
[1
]
Ra
n
-
Zan
W
a
n
g
,
Ch
i
-
F
a
n
g
L
in
,
J
a
-
Ch
e
n
L
in
,
“
Im
a
g
e
h
id
in
g
b
y
o
p
ti
m
a
l
L
S
B
su
b
stit
u
ti
o
n
a
n
d
g
e
n
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ti
c
a
lg
o
rit
h
m
,
”
In
Pa
tt
e
rn
Rec
o
g
n
it
io
n
,
V
o
lu
m
e
3
4
,
Iss
u
e
3
,
p
p
.
6
7
1
-
6
8
3
,
2
0
0
1
.
[2
]
Ch
i
-
Kw
o
n
g
Ch
a
n
∗
,
L
.
M
.
Ch
e
n
g
,
“
Hid
in
g
d
a
ta
in
im
a
g
e
s
b
y
si
m
p
le
L
S
B
su
b
stit
u
ti
o
n
”
,
De
p
a
rtme
n
t
o
f
C
o
mp
u
ter
En
g
i
n
e
e
rin
g
a
n
d
I
n
fo
rm
a
ti
o
n
T
e
c
h
n
o
lo
g
y
,
Cit
y
Un
ive
rs
it
y
o
f
Ho
n
g
Ko
n
g
,
Ho
n
g
Ko
n
g
,
A
u
g
u
st 2
0
0
3
.
[3
]
Dr.
M
.
Um
a
m
a
h
e
s
wa
ri
P
ro
f
.
S
.
S
i
v
a
su
b
ra
m
a
n
ian
S
.
P
a
n
d
iara
jan
,
“
A
n
a
l
y
si
s o
f
Diffe
re
n
t
S
teg
a
n
o
g
ra
p
h
ic A
lg
o
rit
h
m
s
f
o
r
S
e
c
u
re
d
Da
ta
Hid
i
n
g
,
”
IJ
CS
NS
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
C
o
mp
u
ter
S
c
ien
c
e
a
n
d
Ne
two
rk
S
e
c
u
rity
,
V
OL
.
1
0
No
.
8
,
A
u
g
u
st 2
0
1
0
.
[4
]
L
e
e
,
Ye
u
a
n
-
Ku
e
n
,
a
n
d
L
in
g
-
Hw
e
i
Ch
e
n
.
"
Hig
h
c
a
p
a
c
it
y
ima
g
e
ste
g
a
n
o
g
ra
p
h
ic
m
o
d
e
l,
"
IEE
Pro
c
e
e
d
in
g
s
-
Vi
si
o
n
,
Ima
g
e
a
n
d
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
1
4
7
.
3
,
p
p
.
2
8
8
-
2
9
4
,
2
0
0
0
.
[5
]
W
a
n
g
,
S
h
e
n
,
B
ian
Ya
n
g
,
a
n
d
Xia
m
u
Niu
.
"
A
se
c
u
re
ste
g
a
n
o
g
ra
p
h
y
m
e
th
o
d
b
a
se
d
o
n
g
e
n
e
ti
c
a
lg
o
rit
h
m
.
"
J
o
u
rn
a
l
o
f
In
fo
rm
a
t
io
n
Hid
in
g
a
n
d
M
u
lt
ime
d
ia
S
ig
n
a
l
Pro
c
e
ss
in
g
1
,
n
o
.
1
,
28
-
35
,
2
0
1
0
.
[6
]
Ku
m
a
r,
A
rv
in
d
,
a
n
d
Km
P
o
o
ja.
"
S
teg
a
n
o
g
ra
p
h
y
-
A
d
a
ta
h
id
in
g
tec
h
n
iq
u
e
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
mp
u
ter
Ap
p
li
c
a
ti
o
n
s
9
,
n
o
.
7
,
19
-
23
,
2
0
1
0
.
[7
]
M
o
rk
e
l,
T
a
y
a
n
a
,
Ja
n
HP
El
o
f
f
,
a
n
d
M
a
rti
n
S
.
Oliv
ier.
"
A
n
o
v
e
r
v
i
e
w
o
f
i
m
a
g
e
ste
g
a
n
o
g
ra
p
h
y
,
"
In
IS
S
A
,
p
p
.
1
-
1
1
.
2
0
0
5
.
[8
]
M
c
A
n
d
re
w
,
A
l
a
sd
a
ir.
"
A
n
in
tr
o
d
u
c
t
io
n
to
d
ig
it
a
l
im
a
g
e
p
ro
c
e
ss
in
g
w
it
h
m
a
tl
a
b
n
o
tes
f
o
r
s
c
m
2
5
1
1
im
a
g
e
p
ro
c
e
ss
in
g
.
"
S
c
h
o
o
l
o
f
C
o
mp
u
ter
S
c
ien
c
e
a
n
d
M
a
t
h
e
ma
ti
c
s,
Vi
c
t
o
ri
a
Un
ive
rs
it
y
o
f
T
e
c
h
n
o
lo
g
y
2
6
4
(
2
0
0
4
).
[9
]
Ra
b
b
a
n
i,
M
a
ji
d
,
a
n
d
P
a
u
l
W
.
Jo
n
e
s.
Dig
it
a
l
ima
g
e
c
o
mp
re
ss
io
n
tec
h
n
i
q
u
e
s
.
V
o
l.
7
.
S
P
IE
P
re
ss
,
1
9
9
1
.
[1
0
]
S
in
g
h
,
M
a
n
jari,
S
u
sh
il
Ku
m
a
r,
a
n
d
S
id
d
h
a
rth
S
i
n
g
h
.
"
V
a
ri
o
u
s
I
m
a
g
e
Co
m
p
re
ss
io
n
T
e
c
h
n
iq
u
e
s:
L
o
ss
y
a
n
d
L
o
ss
les
s
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
m
p
u
ter
A
p
p
l
ica
ti
o
n
s (
0
9
7
5
–
8
8
8
7
)
V
o
l
u
m
e
1
4
2
–
No
.
6
,
M
a
y
2
0
1
6
.
[1
1
]
Ra
id
,
A
.
M
.
,
W
.
M
.
Kh
e
d
r,
M
.
A
.
El
-
Do
su
k
y
,
a
n
d
W
e
s
a
m
A
h
m
e
d
.
"
JP
EG
i
m
a
g
e
c
o
m
p
re
ss
io
n
u
sin
g
d
isc
re
te
c
o
sin
e
tran
sf
o
r
m
-
A
S
u
rv
e
y
,
"
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Co
mp
u
ter
S
c
ien
c
e
&
En
g
in
e
e
rin
g
S
u
rv
e
y
(
IJ
CS
ES
)
Vo
l.
5
,
No
.
2
,
p
p
.
3
9
-
47
,
A
p
ril
2
0
1
4
.
[1
2
]
Ch
o
w
d
h
u
ry
,
M
.
M
o
z
a
m
m
e
l
Ho
q
u
e
,
a
n
d
Am
in
a
Kh
a
tu
n
.
"
I
m
a
g
e
c
o
m
p
re
ss
io
n
u
si
n
g
d
i
sc
re
te
w
a
v
e
let
tran
sf
o
r
m
,
"
IJ
C
S
I
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
C
o
mp
u
ter
S
c
ien
c
e
Iss
u
e
s
9
,
n
o
.
4
,
p
p
.
3
2
7
-
3
3
0
,
2
0
1
2
.
[1
3
]
Am
in
,
M
u
h
a
li
m
M
o
h
a
m
e
d
,
M
a
z
lee
n
a
S
a
ll
e
h
,
S
u
b
a
riah
Ib
ra
h
im
,
M
o
h
d
Ro
z
i
Ka
tm
in
,
a
n
d
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