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1
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d
m
ess
ag
e
s
.
T
h
e
is
s
u
e
o
f
r
o
b
u
s
tn
ess
is
cr
u
cial
in
wh
e
n
wate
r
m
ar
k
in
g
tech
n
iq
u
es
ar
e
u
s
ed
b
ec
au
s
e
o
f
c
o
p
y
r
ig
h
t
p
r
o
tectio
n
[
4
]
.
T
h
e
n
o
tio
n
o
f
im
p
er
ce
p
tib
ilit
y
is
s
y
n
o
n
y
m
o
u
s
with
u
n
d
ec
tab
ilit
y
,
wh
ich
ca
n
b
e
ca
lcu
lated
u
s
in
g
v
a
r
io
u
s
im
a
g
e
q
u
ality
m
e
asu
r
em
en
t
m
etr
ics
,
s
u
ch
as p
ea
k
-
s
ig
n
al
-
to
-
n
o
is
e
-
r
at
io
(
PS
NR
)
[5
]
,
[
6
]
.
T
h
e
co
r
r
elatio
n
b
etwe
en
h
id
i
n
g
p
ay
lo
a
d
ca
p
ac
ity
(
PC
)
an
d
q
u
ality
o
f
s
teg
o
m
ed
ia
(
SM
)
is
p
u
r
ely
d
escr
ib
ed
v
ia
a
b
alan
ce
wh
ich
au
th
o
r
s
attem
p
t
to
ac
h
iev
e.
M
o
s
t
o
f
ten
,
th
e
q
u
ality
o
f
s
teg
o
m
ed
iu
m
is
r
ed
u
ce
d
b
y
co
n
ce
alm
en
t
o
f
h
u
g
e
am
o
u
n
ts
o
f
d
ata
with
in
a
c
o
v
er
m
ed
iu
m
.
C
o
n
s
eq
u
en
tly
,
h
id
i
n
g
ca
p
ac
ities
h
av
e
co
n
tin
u
ed
to
r
em
ai
n
co
m
p
ar
ativ
ely
lo
w
b
ec
au
s
e
o
f
th
is
n
eg
ativ
e
ef
f
ec
t
o
n
th
e
q
u
ality
o
f
s
teg
o
[
7
]
.
W
ith
r
esp
ec
t
to
m
ec
h
an
is
m
f
o
r
em
b
e
d
d
in
g
,
th
e
tech
n
iq
u
es
o
f
s
teg
an
o
g
r
ap
h
y
ar
e
p
ar
titi
o
n
ed
t
o
two
im
p
o
r
tan
t
class
es,
wh
ich
ar
e
s
p
atial
-
d
o
m
ain
(
SD)
an
d
tr
an
s
f
o
r
m
-
d
o
m
ain
(
T
D)
.
R
e
g
ar
d
less
o
f
th
e
ad
v
an
tag
es
p
r
o
v
id
ed
b
y
cu
r
r
e
n
t
m
eth
o
d
s
,
p
r
o
b
lem
s
s
u
c
h
as:
i
)
th
e
u
s
e
o
f
i
n
ad
eq
u
ate
em
b
e
d
d
in
g
alg
o
r
ith
m
s
m
ay
g
en
er
at
e
v
is
u
ally
d
is
to
r
ted
s
teg
o
im
ag
es
(
SI)
,
w
h
ich
in
tu
r
n
in
cr
ea
s
es
th
e
lik
elih
o
o
d
o
f
h
u
m
a
n
v
is
u
al
s
y
s
te
m
d
etec
tio
n
,
an
d
ii
)
im
b
alan
ce
b
etwe
en
im
ag
e
q
u
ality
,
co
m
p
u
tatio
n
al
co
m
p
lex
ity
,
ca
p
ac
ity
f
o
r
p
ay
lo
ad
an
d
s
ec
u
r
ity
;
th
u
s
,
m
ak
in
g
th
em
i
n
ap
p
r
o
p
r
iate.
T
h
is
s
tu
d
y
,
th
e
u
s
e
o
f
o
u
r
m
ec
h
an
is
m
alo
n
g
s
id
e
w
ith
ch
ao
tic
m
eth
o
d
is
em
p
lo
y
e
d
in
d
ev
elo
p
in
g
a
n
ef
f
icien
t sch
e
m
e
in
s
p
atial
d
o
m
ai
n
,
with
th
e
aim
o
f
a
d
d
r
ess
in
g
th
e
af
o
r
em
en
tio
n
ed
p
r
o
b
lem
s
.
T
h
is
p
ap
er
m
a
k
es
th
e
f
o
llo
win
g
k
ey
c
o
n
tr
ib
u
tio
n
s
:
i)
i
n
tr
o
d
u
ce
an
ef
f
ec
tiv
e
d
ig
ital
im
ag
e
s
teg
an
o
g
r
a
p
h
y
with
ac
h
iev
i
n
g
a
g
o
o
d
q
u
ality
o
f
i
m
ag
e,
p
ay
lo
ad
an
d
s
ec
u
r
ity
;
ii
)
i
d
en
tif
y
th
e
r
a
n
d
o
m
p
ix
el
u
s
ed
to
em
b
e
d
h
i
d
d
en
in
f
o
r
m
atio
n
,
wh
ile
th
e
r
a
n
d
o
m
f
u
n
ctio
n
is
u
s
ed
to
b
o
o
s
t
th
e
s
y
s
tem
'
s
r
esil
ien
ce
ag
ain
s
t
tr
ac
k
er
s
'
attem
p
ts
to
d
is
co
v
er
wh
ich
p
ix
el
to
em
b
ed
; iii)
t
h
e
em
b
ed
d
in
g
o
f
th
e
s
ec
r
et
in
f
o
r
m
atio
n
is
d
o
n
e
i
n
a
r
an
d
o
m
r
e
g
io
n
with
in
an
im
ag
e
th
r
o
u
g
h
t
h
e
u
s
e
o
f
th
e
s
p
atial
-
d
o
m
ain
(
SD)
o
f
th
e
co
v
e
r
-
im
ag
e
(
C
I
)
u
s
in
g
t
h
e
o
d
d
/ev
en
p
i
x
el
allo
ca
tio
n
.
T
h
is
way
,
th
e
q
u
ali
ty
o
f
t
h
e
s
teg
o
-
im
a
g
es
is
b
o
o
s
ted
wh
ile
an
e
x
tr
ac
tio
n
o
f
t
h
e
s
ec
r
et
d
ata
is
m
ad
e
d
if
f
icu
lt
2.
P
RE
L
I
M
I
NAR
I
E
S
2
.
1
.
L
ea
s
t
-
s
ig
nifica
nt
-
bit
L
S
B
s
u
bs
t
it
utio
n
T
h
e
r
ep
r
esen
tatio
n
o
f
least
-
s
ig
n
if
ican
t
-
b
it (
L
SB
)
co
n
s
id
er
s
ea
s
y
an
d
co
n
v
en
tio
n
al
p
r
o
ce
s
s
ap
p
lied
f
o
r
in
s
er
tin
g
s
ec
r
et
d
ata
en
clo
s
ed
b
y
c
o
v
er
ed
im
ag
e
[
8
]
.
T
h
o
u
g
h
th
is
p
r
o
ce
s
s
co
n
tin
u
es,
it
is
th
i
n
k
ab
le
t
o
o
v
er
wr
ite
th
e
d
ep
ictio
n
o
f
b
i
n
ar
y
s
ec
r
et
d
ata.
C
o
n
ce
r
n
in
g
to
th
e
g
r
ay
s
ca
le
im
ag
es
th
at
p
ix
els
h
av
e
v
alu
es
ju
s
t
s
in
g
le
r
an
g
in
g
(
0
to
2
5
5
)
with
an
8
b
i
ts
d
ep
th
,
th
ese
s
ec
r
et
in
f
o
r
m
ati
o
n
b
its
d
o
n
o
t
co
n
v
er
t
in
to
b
i
n
ar
y
b
its
d
u
e
to
th
eir
d
ir
ec
tly
u
s
in
g
to
s
u
b
s
titu
te
th
e
co
v
er
im
ag
e
o
f
th
e
o
b
jects.
W
ith
r
ef
er
r
in
g
to
co
lo
r
im
ag
es
wh
ich
h
o
ld
3
r
o
u
tes
r
ed
,
g
r
ee
n
,
an
d
b
lu
e
(
R
GB
)
b
esid
es
2
4
b
its
d
ep
th
,
th
en
a
c
o
v
er
o
b
ject
(
im
ag
e
)
ca
n
b
e
o
r
ig
in
ally
p
ar
titi
o
n
i
n
g
in
to
3
ch
a
n
n
els ju
s
t a
s
ec
r
et
d
ata
is
em
b
ed
d
ed
ea
r
l
y
in
ea
ch
c
h
an
n
el.
T
h
en
,
th
ese
th
r
e
e
p
ath
s
will b
e
m
er
g
ed
i
n
o
r
d
er
t
o
cr
ea
te
t
h
e
SI.
T
h
e
L
SB
b
its
m
o
d
if
icatio
n
m
ay
n
o
t
b
e
allo
wed
t
h
e
h
u
m
an
v
is
u
al
s
y
s
tem
(
HVS
)
f
o
r
d
etec
tin
g
th
e
s
teg
o
-
im
ag
e.
Owin
g
to
th
e
f
ac
t
o
f
L
SB
s
u
b
s
titu
tio
n
m
eth
o
d
as
d
is
cr
ete
k
in
d
is
em
p
lo
y
ed
in
th
e
s
u
g
g
ested
s
y
s
tem
,
th
e
m
ath
em
atica
l
ex
p
r
ess
io
n
f
o
r
th
is
m
eth
o
d
ca
n
b
e
p
r
ep
ar
e
d
with
ac
ce
p
tab
le
d
etails.
A
m
ath
em
atica
l
ex
p
r
ess
io
n
aim
s
f
o
r
p
r
o
v
id
i
n
g
d
ee
p
er
p
e
r
ce
p
ti
o
n
o
n
t
h
e
f
o
ca
l
th
o
u
g
h
t
o
f
t
h
e
s
ch
em
e
in
th
e
n
ex
t
s
ec
tio
n
.
T
h
e
ass
o
r
ted
L
SB
em
b
ed
d
in
g
p
er
ce
n
tag
e
(
E
P)
co
n
tain
s
6
.
2
5
%,
1
2
.
5
%,
1
8
.
7
5
%
in
ad
d
itio
n
to
2
5
%,
th
at
in
ten
d
s
0
.
5
,
1
.
0
,
1
.
5
,
a
n
d
2
b
p
p
r
esp
ec
tiv
ely
m
a
y
b
e
u
tili
ze
d
d
ep
en
d
o
n
th
e
em
b
ed
d
e
d
.
B
y
u
s
in
g
a
s
im
p
le
in
s
tan
ce
,
an
in
clu
s
iv
e
d
escr
ip
ti
o
n
o
f
th
e
f
u
n
d
am
en
tal
co
n
ce
p
t
o
f
th
e
L
SB
s
teg
an
o
g
r
ap
h
y
b
asi
s
ca
n
b
e
p
r
o
v
i
d
in
g
.
I
f
a
1
2
.
5
%
E
P
ex
am
p
le
is
co
n
s
id
er
ed
,
th
at
is
m
ea
n
1
b
p
p
in
e
ac
h
L
SB
,
an
d
ca
n
b
e
e
x
ten
d
e
d
to
an
o
th
er
E
P.
W
ith
s
u
ch
im
p
lem
en
tatio
n
,
a
s
teg
o
im
ag
e
im
p
er
c
ep
tib
ilit
y
is
d
e
cr
ea
s
ed
,
th
u
s
m
ak
i
n
g
it
s
im
p
l
e
f
o
r
t
h
e
HVS
f
o
r
n
o
ticin
g
th
e
s
teg
o
-
im
ag
e.
At
th
is
tim
e,
im
ag
e
q
u
ality
will b
e
co
m
p
r
o
m
is
in
g
f
o
r
d
ata
ca
p
ac
i
ty
.
W
h
en
d
ata
with
lar
g
er
a
m
o
u
n
t
is
co
v
er
ed
,
an
i
m
ag
e
q
u
ality
d
eg
r
a
d
atio
n
is
a
r
is
in
g
.
B
y
u
s
in
g
L
SB
m
eth
o
d
s
,
th
e
ca
p
a
city
with
h
ig
h
d
ata
ca
n
b
e
ac
h
iev
e
d
.
Fig
u
r
e
1
s
h
o
ws
v
ar
io
u
s
s
teg
o
im
ag
es
o
f
L
en
a
in
d
if
f
er
e
n
t
em
b
ed
d
in
g
p
er
ce
n
tag
es
[
9
]
-
[
1
1
]
.
T
h
r
o
u
g
h
th
e
r
an
d
o
m
a
d
d
itio
n
o
f
1
to
th
e
g
r
ay
lev
els
o
n
t
h
e
C
I
,
th
e
p
ix
els
o
f
th
e
im
a
g
e
a
r
e
s
lig
h
tly
m
o
d
if
ied
u
s
in
g
th
e
L
SB
-
m
atc
h
in
g
.
T
h
is
is
d
o
n
e
if
t
h
er
e
is
n
o
co
r
r
esp
o
n
d
en
ce
b
etwe
en
t
h
e
s
ec
r
et
b
it
an
d
th
e
L
SB
o
f
a
g
i
v
en
p
ix
el,
with
th
e
v
alu
es
o
f
th
e
p
ix
els
m
ain
tain
e
d
with
in
th
e
r
an
g
e
o
f
0
-
2
5
5
.
T
h
er
e
is
n
o
d
if
f
er
en
ce
b
etwe
en
th
e
p
r
o
ce
s
s
o
f
ex
tr
a
ct
io
n
in
L
SB
an
d
L
SB
-
M,
th
is
m
ea
n
s
to
u
s
e
a
s
h
ar
ed
s
ec
r
et
k
ey
to
o
b
tain
a
tr
av
er
s
in
g
r
o
u
te,
as
well
as
to
ex
tr
ac
t
th
e
L
SB
o
f
ea
ch
p
ix
el
f
o
r
o
b
tain
i
n
g
r
ea
l
em
b
ed
d
e
d
b
its
.
A
p
air
o
f
p
ix
els
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
6
9
4
-
705
696
(
,
+
1
)
is
u
s
ed
b
y
least
s
ig
n
if
ican
t
b
it
m
atch
in
g
r
ev
is
ited
(
L
SB
-
MR
)
[
1
2
]
as
an
em
b
ed
d
i
n
g
u
n
it
th
at
is
m
an
ip
u
lated
to
(
′
,
′
+
1
)
in
a
way
to
m
ak
e
cr
iter
ia
is
s
atis
f
ied
.
{
(
′
)
=
S
(
|
′
2
|
+
′
+
1
)
=
S
+
1
}
(
1
)
W
h
er
e
an
d
+
1
d
en
o
tes
th
e
em
b
ed
d
in
g
u
n
it
wh
ile
th
e
two
s
ec
r
et
b
its
ar
e
r
e
p
r
esen
ted
b
y
an
d
S
+
1
.
W
ith
th
is
co
r
r
elatio
n
,
th
e
L
SB
an
d
L
SB
-
M
s
u
ch
as
ir
r
eg
u
lar
a
r
tifa
cts
ar
t
d
o
es
n
o
t
f
o
r
m
e
d
in
s
teg
o
im
ag
es.
Mo
r
e
s
o
,
with
th
e
u
s
e
o
f
L
SB
-
MR,
th
e
r
ate
at
wh
ich
th
e
p
i
x
els
ar
e
m
o
d
if
ied
in
ca
n
b
e
m
i
n
im
ized
in
v
ar
ian
ce
m
eth
o
d
with
L
SB
an
d
L
S
B
-
M.
T
h
e
p
r
o
ce
d
u
r
e
o
f
ex
tr
ac
tio
n
in
v
o
l
v
es
th
e
g
en
er
atio
n
o
f
a
tr
av
e
r
s
in
g
p
ath
u
tili
zin
g
a
s
ec
r
et
k
ey
(
SK
)
as
well
as
a
q
u
asi
-
r
an
d
o
m
-
n
u
m
b
er
-
g
en
er
ato
r
,
an
d
af
ter
war
d
s
th
e
ex
tr
ac
tio
n
o
f
two
b
its
f
r
o
m
ea
ch
o
f
th
e
u
n
its
o
f
e
m
b
ed
d
in
g
is
p
er
f
o
r
m
ed
.
1
2
.
5
% E
P=1
.
5
b
p
p
2
5
% E
P=2
b
p
p
5
0
% E
P=4
b
p
p
6
2
.
5
% E
P=5
b
p
p
Fig
u
r
e
1
.
T
h
e
im
p
er
ce
p
tib
ilit
y
o
f
L
en
a
s
teg
o
-
im
ag
e
(
SI)
u
s
in
g
d
if
f
er
e
n
t E
P [
1
2
]
I
n
a
s
tu
d
y
ca
r
r
ied
o
u
t
b
y
B
h
a
r
d
waj
an
d
Sh
ar
m
a
b
[
1
3
]
,
attem
p
ts
wer
e
m
ad
e
to
im
p
r
o
v
e
t
h
e
s
ec
u
r
ity
an
d
d
is
tr
ib
u
te
th
e
m
ess
ag
e
with
in
th
e
en
tire
h
o
s
t
im
ag
e.
T
o
ac
h
iev
e
th
is
,
th
ese
r
esear
ch
er
s
in
v
esti
g
ated
th
e
s
im
u
latio
n
o
f
im
ag
es
th
r
o
u
g
h
th
e
u
s
e
o
f
tex
t,
an
d
th
ey
u
s
ed
L
SB
to
h
id
e
in
f
o
r
m
atio
n
.
Acc
o
r
d
in
g
to
th
em
,
th
e
aim
o
f
th
eir
s
tu
d
y
is
to
p
r
o
v
id
e
th
r
ee
lev
el
s
ec
u
r
ity
in
wh
ich
th
e
s
ec
r
et
m
ess
ag
e
i
s
co
m
p
lem
en
ted
,
th
e
co
m
p
lem
en
ted
s
ec
r
et
m
ess
ag
e
is
h
id
d
en
with
in
a
co
v
er
im
a
g
e
p
ix
el
th
at
ar
e
s
elec
ted
r
an
d
o
m
ly
th
r
o
u
g
h
th
e
u
s
e
o
f
a
p
s
eu
d
o
r
a
n
d
o
m
n
u
m
b
er
o
f
g
en
er
ato
r
an
d
in
v
er
t
e
d
b
it
L
S
B
m
eth
o
d
.
B
ased
o
n
t
h
e
r
esu
lts
o
f
th
eir
s
tu
d
y
,
th
eir
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
o
u
t
p
er
f
o
r
m
s
th
e
co
n
v
e
n
tio
n
al
L
SB
as
well
as
th
e
in
v
er
s
e
L
SB
with
lo
wer
m
ea
n
s
q
u
a
r
e
er
r
o
r
(
MSE
)
an
d
h
i
g
h
er
PS
NR
.
Hash
im
et
a
l.
[
1
4
]
in
th
eir
s
tu
d
y
,
p
r
o
p
o
s
ed
a
s
ec
u
r
e
im
ag
e
s
te
g
an
o
g
r
ap
h
y
cr
ea
ted
b
y
Hu
f
f
m
an
co
d
in
g
,
d
is
tr
ib
u
tio
n
o
f
o
d
d
/ev
e
n
,
a
n
d
Hen
o
n
m
ap
.
T
h
e
im
p
lem
en
tat
io
n
o
f
th
e
p
r
o
p
o
s
ed
f
r
am
ew
o
r
k
h
as
b
ee
n
f
o
u
n
d
to
b
e
less
co
m
p
lex
in
co
n
tr
ast
to
o
th
er
cu
r
r
en
t
m
eth
o
d
s
.
Usi
n
g
th
e
Hen
o
n
m
a
p
alg
o
r
ith
m
,
th
e
im
p
er
ce
p
tib
ilit
y
o
f
th
e
s
teg
o
-
im
ag
e
is
in
cr
ea
s
ed
b
y
u
s
in
g
p
ix
el
d
is
tr
ib
u
tio
n
in
o
r
d
er
to
g
et
a
b
etter
p
r
o
tectio
n
m
eth
o
d
.
Prio
r
to
t
h
e
p
r
o
ce
s
s
o
f
em
b
ed
d
i
n
g
,
th
e
s
ec
r
et
m
ess
ag
e
is
em
b
ed
d
ed
u
s
i
n
g
H
u
f
f
m
an
c
o
d
in
g
.
T
wo
m
a
in
r
ea
s
o
n
s
th
at
th
is
m
eth
o
d
h
as
alwa
y
s
b
ee
n
s
ee
n
ef
f
icien
t:
th
e
f
ir
s
t
is
th
at
d
u
r
i
n
g
th
e
em
b
e
d
d
in
g
p
r
o
ce
s
s
it
is
ab
le
to
ch
e
ck
th
e
co
r
r
esp
o
n
d
en
ce
b
etwe
en
s
ec
r
e
t
b
its
with
L
SB
in
o
r
d
er
to
d
eter
m
in
e
1
an
d
0
,
an
d
th
e
s
ec
o
n
d
i
s
th
e
s
eg
m
en
tatio
n
o
f
th
e
s
ec
r
et
m
ess
ag
e
in
o
r
d
er
to
tr
ac
k
an
d
m
ap
ev
e
r
y
b
it
with
in
th
e
s
teg
o
im
ag
e.
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
t
h
ei
r
s
u
g
g
ested
p
r
o
t
o
co
l is b
etter
th
an
co
m
p
a
r
in
g
to
[
1
5
]
,
[
1
6
]
i
n
t
er
m
s
o
f
PS
NR
,
b
ased
o
n
th
e
f
in
d
in
g
s
.
Sin
g
h
an
d
Data
r
[
1
7
]
p
r
esen
ted
an
im
ag
e
s
teg
an
o
g
r
a
p
h
y
cr
ea
ted
with
wav
elet
tr
a
n
s
f
o
r
m
atio
n
an
d
R
C
4
alg
o
r
ith
m
s
.
A
p
r
o
p
o
s
ed
m
eth
o
d
with
co
v
er
im
ag
e
is
ap
p
o
r
ti
o
n
ed
in
t
o
6
4
b
lo
ck
s
o
f
(
8
×
8
)
with
u
s
ef
u
l
wav
elet
tr
an
s
f
o
r
m
.
T
h
e
s
ec
r
et
m
ess
ag
e
h
er
e
en
cr
y
p
ted
ea
r
lier
b
y
em
b
ed
d
in
g
with
R
C
4
alg
o
r
ith
m
is
u
s
ed
f
o
r
en
h
an
cin
g
th
e
s
ec
u
r
ity
lev
els.
T
h
e
Steg
o
im
ag
e
n
o
w
is
d
if
f
icu
lt
f
o
r
d
e
tect
b
y
HVS
attac
k
.
Patel
an
d
C
h
ee
r
an
[
1
8
]
h
a
d
em
p
lo
y
ed
an
d
in
v
esti
g
ated
th
e
s
teg
an
o
g
r
a
p
h
y
tech
n
i
q
u
e
a
n
d
ad
v
an
ce
d
en
cr
y
p
tio
n
s
tan
d
ar
d
(
AE
S
)
alg
o
r
ith
m
in
o
r
d
er
to
p
r
o
d
u
ce
an
ass
ess
m
en
t
an
d
co
m
p
ar
is
o
n
in
to
v
ar
i
o
u
s
im
ag
es
f
o
r
m
at
an
d
allo
w
s
m
o
s
t
ap
p
r
o
p
r
iate
in
f
o
r
m
atio
n
with
th
is
p
r
o
ce
d
u
r
e.
L
SB
s
u
b
s
titu
tio
n
alg
o
r
ith
m
s
wer
e
u
s
ed
f
o
r
im
p
lem
e
n
tin
g
t
h
is
Steg
an
o
g
r
ap
h
y
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
ec
u
r
ity
a
n
d
imp
ercep
tib
ilit
y
i
mp
r
o
vin
g
o
f ima
g
e
s
teg
a
n
o
g
r
a
p
h
y
…
(
N
o
o
r
A
lh
u
d
a
F
.
A
b
b
a
s
)
697
m
eth
o
d
.
An
in
v
esti
g
atio
n
an
d
ev
alu
atio
n
wer
e
co
m
p
leted
wit
h
d
if
f
er
en
t
p
a
r
am
eter
s
lik
e
d
elay
,
PS
NR
,
M
SE,
in
ad
d
itio
n
to
a
b
s
o
lu
te
m
ea
n
s
q
u
ar
e
er
r
o
r
(
AM
SE)
.
A
n
ew
r
ev
er
s
ib
le
m
eth
o
d
o
f
d
ata
h
id
in
g
u
tili
zin
g
p
ix
el
-
v
alu
e
-
d
iffer
en
ce
(
PVD)
with
d
iffer
en
tial
ex
p
an
s
io
n
(
DE
)
wer
e
p
r
esen
te
d
b
y
J
an
a
et
a
l.
(
2
0
1
6
)
.
T
h
e
s
ec
r
et
m
ess
ag
e
in
itially
s
ep
a
r
ated
in
to
s
u
b
-
s
tr
ea
m
with
n
b
its
s
ize
in
p
r
o
jecte
d
m
eth
o
d
.
PVD
ca
n
b
e
a
p
p
lied
f
o
r
em
b
ed
d
in
g
n
-
1
b
its
in
a
d
d
itio
n
to
em
b
ed
1
b
it b
y
ap
p
ly
in
g
d
iffer
en
ce
-
ex
p
a
n
s
io
n
(
DE
)
.
L
astl
y
,
b
ased
o
n
th
e
s
h
ar
in
g
s
ec
r
et
k
ey
b
it
s
tr
ea
m
,
a
p
air
o
f
two
-
s
teg
o
p
ix
els
will
b
e
d
is
tr
ib
u
ted
am
o
n
g
d
u
al
im
a
g
e.
An
e
x
tr
ac
tin
g
te
ch
n
iq
u
e
c
o
n
s
id
er
s
a
s
am
e
em
b
ed
tech
n
iq
u
e
to
th
at
o
f
r
ev
e
r
s
e
s
en
s
in
g
[
1
9
]
.
T
h
e
s
ec
u
r
in
g
co
lo
r
im
ag
e
s
teg
an
o
g
r
a
p
h
y
b
ased
o
n
L
SB
was r
ec
o
m
m
en
d
ed
b
y
Al
-
T
a
m
im
i
et
a
l.
[
2
0
]
.
T
h
ey
u
s
ed
asy
m
m
etr
ic
k
ey
i
n
th
e
im
ag
e
s
teg
an
o
g
r
ap
h
y
f
o
r
L
SB
s
ch
em
e
wh
ich
co
n
tain
s
3
2
in
teg
er
s
ar
r
ay
.
I
n
s
er
tin
g
o
f
d
ata
h
id
in
g
is
r
a
n
d
o
m
in
r
elate
d
to
h
i
d
in
g
m
ess
ag
e
an
d
p
ix
el
s
elec
tio
n
g
en
e
r
a
to
r
,
th
e
ap
p
ly
i
n
g
o
f
tr
an
s
p
o
s
itio
n
is
d
o
n
e
f
o
r
ea
ch
2
4
-
b
its
b
lo
ck
.
A
s
ec
u
r
i
ty
h
as
b
ee
n
im
p
r
o
v
e
d
with
L
SB
s
u
b
s
titu
tio
n
tech
n
iq
u
e.
Acc
o
r
d
in
g
to
th
e
liter
atu
r
e
r
ev
iew,
th
e
m
ajo
r
ity
o
f
c
u
r
r
e
n
t
s
teg
an
o
g
r
ap
h
y
tech
n
o
lo
g
ie
s
ar
e
in
ca
p
ab
le
o
f
g
en
er
atin
g
h
ig
h
-
q
u
ality
s
teg
o
-
i
m
ag
es,
leav
in
g
th
e
s
u
b
ject
v
u
l
n
er
ab
le
to
id
en
tific
atio
n
b
y
h
u
m
an
v
i
s
io
n
s
y
s
tem
s
.
C
o
n
s
eq
u
en
tly
,
th
e
h
id
d
en
s
ec
r
et
ca
n
b
e
ea
s
ily
ac
ce
s
s
ed
b
y
t
h
e
attac
k
er
s
,
a
n
d
t
h
er
ef
o
r
e,
ca
n
n
o
t
b
e
u
s
ed
as
a
n
au
th
en
tic
in
f
o
r
m
atio
n
i
n
to
p
-
s
ec
r
et
s
ec
u
r
ity
s
y
s
tem
s
.
2
.
2
.
Ra
nd
o
m
ma
p f
un
ct
io
n
On
e
o
f
t
h
e
m
ajo
r
r
ea
s
o
n
s
'
s
teg
an
o
g
r
a
p
h
y
is
d
ev
elo
p
ed
is
to
af
f
o
r
d
an
e
n
v
ir
o
n
m
en
t
wh
ich
is
s
ec
u
r
ed
,
wh
er
e
d
ata
ca
n
b
e
tr
an
s
m
itted
o
v
er
t
h
e
n
etwo
r
k
b
y
s
ec
r
et
m
ess
ag
es
in
s
teg
o
-
im
ag
es
ty
p
e.
T
h
e
in
c
r
ea
s
in
g
co
n
ce
r
n
a
b
o
u
t
th
e
s
ec
u
r
ity
o
f
d
ata
is
o
n
e
o
f
th
e
m
ain
m
o
tiv
a
tio
n
s
o
f
th
is
r
esear
ch
.
Ma
n
y
s
t
u
d
ies
wer
e
ex
ec
u
ted
in
th
e
s
teg
an
o
g
r
ap
h
y
f
ield
with
a
p
u
r
p
o
s
e
o
f
d
ev
elo
p
ed
n
o
v
el
ap
p
r
o
ac
h
es
th
r
o
u
g
h
w
h
ich
b
y
s
teg
an
o
g
r
a
p
h
y
a
m
ess
ag
e
ca
n
b
e
s
ec
u
r
e
d
[
2
1
]
.
W
ith
r
esp
ec
t
to
en
h
a
n
ce
d
at
a
p
ar
ticu
lar
ity
,
v
ar
io
u
s
s
tu
d
ies
d
ea
l
with
r
an
d
o
m
tech
n
iq
u
e
d
u
e
to
th
eir
h
ig
h
er
ef
f
icien
cy
an
d
s
im
p
le
u
s
in
g
.
Ad
v
an
tag
es
o
f
r
an
d
o
m
izin
g
alg
o
r
ith
m
s
ca
n
b
e
s
u
m
m
ar
ized
as:
i)
q
u
ick
an
d
co
m
f
o
r
t,
o
r
m
ay
b
e
b
o
th
i
n
ass
o
r
ted
p
r
o
b
lem
s
,
ii)
ea
s
y
em
p
l
o
y
m
en
t,
an
d
iii)
f
ast
an
d
lik
ely
.
Ma
n
y
au
th
o
r
s
wer
e
f
o
u
n
d
in
t
h
e
liter
atu
r
e
h
av
e
lev
e
r
ag
ed
r
a
n
d
o
m
m
ap
f
u
n
c
tio
n
co
m
p
en
s
a
tio
n
s
,
with
ea
ch
b
o
s
s
es
its
lim
itatio
n
s
an
d
s
tr
en
g
th
s
.
Dep
en
d
in
g
o
n
b
eh
a
v
io
r
,
v
ar
io
u
s
k
i
n
d
s
o
f
r
an
d
o
m
m
ap
s
ar
e
ex
is
tin
g
,
s
u
ch
as,
n
u
b
asi [
2
2
]
,
Ar
n
o
ld
s
cr
am
b
les [
2
3
]
,
in
a
d
d
itio
n
to
k
n
ig
h
t to
u
r
[
2
4
]
.
C
o
n
ce
r
n
in
g
n
o
r
m
al
r
an
d
o
m
m
ap
s
,
th
e
s
elec
tio
n
n
u
m
b
e
r
s
ca
n
b
e
co
m
p
leted
b
y
o
n
e
p
ar
am
eter
a
t
o
r
ig
in
al
co
n
d
itio
n
s
[
2
5
]
.
T
w
o
r
a
n
d
o
m
m
a
p
s
ca
n
b
e
u
tili
ze
d
f
o
r
th
e
p
ix
els
allo
ca
tio
n
s
with
th
e
aim
in
g
o
f
p
r
eser
v
in
g
th
e
p
r
o
p
o
s
ed
m
eth
o
d
.
Als
o
,
a
n
o
v
er
lap
b
etwe
en
th
ese
two
way
s
th
at
g
u
ar
an
tee
f
o
r
d
ata
wh
ich
is
i
n
tr
o
d
u
ce
d
ca
n
b
e
en
tire
ly
c
o
n
ce
a
led
an
d
d
is
co
v
er
e
d
th
e
p
ix
els’
p
ath
is
s
o
h
a
r
d
o
r
a
lm
o
s
t im
p
o
s
s
ib
le
[
2
3
]
,
[
2
4
]
,
s
o
th
at,
o
u
r
m
eth
o
d
s
ec
u
r
ity
is
g
u
ar
an
teed
.
2
.
3
.
H
uf
f
ma
n c
o
din
g
T
h
e
m
ain
o
b
jectiv
e
o
f
th
e
H
u
f
f
m
an
co
d
in
g
alg
o
r
ith
m
is
to
r
ed
u
ce
th
e
s
ize
o
f
tex
t
b
ef
o
r
e
em
b
ed
d
in
g
to
th
e
im
ag
e.
As
s
h
o
wn
in
Fig
u
r
e
2
t
h
e
Hu
f
f
m
an
alg
o
r
ith
m
d
e
p
en
d
s
o
n
r
ed
u
cin
g
th
e
f
r
eq
u
e
n
t
letter
s
an
d
g
iv
es
th
em
p
r
io
r
ity
co
d
e
o
r
s
h
o
r
t
p
a
th
in
th
e
H
u
f
f
m
a
n
tr
ee
.
T
h
e
c
ap
ac
ity
is
an
im
p
o
r
tan
t
c
o
n
ce
p
t
in
s
teg
an
o
g
r
ap
h
y
m
eth
o
d
to
m
ak
e
th
e
m
eth
o
d
m
o
r
e
r
o
b
u
s
t,
s
u
ch
as
b
etter
m
eth
o
d
th
at
ca
n
h
o
ld
h
ig
h
am
o
u
n
ts
o
f
d
ata
in
s
id
e
h
o
s
tin
g
im
ag
e
w
h
ile
m
ain
tai
n
in
g
th
e
q
u
ality
o
f
th
e
im
ag
e
r
ep
r
esen
ted
b
y
PS
NR
.
Fo
r
th
e
co
n
ce
p
t
o
f
d
ata
m
an
ag
em
en
t
an
d
tr
a
n
s
f
er
p
r
o
t
o
co
l
co
m
p
r
ess
io
n
o
f
d
ata
tr
an
s
f
er
r
ed
f
r
o
m
s
en
d
er
to
r
ec
eiv
er
i
s
v
er
y
u
s
ef
u
l
b
esid
e
o
th
er
tech
n
i
q
u
es
u
s
ed
in
th
is
r
esear
ch
.
Fig
u
r
e
3
s
h
o
ws
a
s
im
p
le
f
lo
wch
ar
t
o
f
H
u
f
f
m
a
n
co
d
in
g
ap
p
lied
in
th
is
r
esear
ch
.
Hig
h
f
r
e
q
u
en
c
y
in
th
is
ca
s
e
wil
l g
et
less
p
ath
o
f
v
is
itin
g
to
r
ed
u
ce
g
o
in
g
d
ee
p
e
v
e
r
y
tim
e
an
d
l
et
less
f
r
eq
u
e
n
cy
in
t
h
e
d
ee
p
o
f
th
e
tr
ee
,
th
en
will g
ain
m
a
n
y
clo
c
k
s
in
d
ig
ital w
o
r
d
as 0
,
1
.
Fig
u
r
e
2
.
R
ed
u
ce
tex
t f
r
e
q
u
en
cy
in
H
u
f
f
m
an
c
o
d
in
g
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
6
9
4
-
705
698
Fig
u
r
e
3
.
Flo
wch
ar
t
o
f
H
u
f
f
m
an
co
d
in
g
3.
T
H
E
P
RO
P
O
SE
D
M
E
T
H
O
D
T
h
is
s
ec
tio
n
p
r
o
v
id
es
a
g
r
ap
h
i
c
d
escr
ip
tio
n
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
wh
ich
is
p
r
o
p
o
s
ed
in
th
is
s
tu
d
y
alo
n
g
s
id
e
its
k
ey
m
o
d
u
les.
T
h
e
in
v
en
tio
n
o
f
th
e
m
et
h
o
d
o
lo
g
y
is
f
u
r
th
er
clar
if
ie
d
b
y
th
is
g
r
ap
h
ic
r
ep
r
esen
tatio
n
o
f
th
e
f
r
am
ewo
r
k
,
as
th
en
r
e
ad
er
s
ca
n
g
et
a
b
etter
im
ag
e
an
d
a
g
r
ea
ter
u
n
d
er
s
tan
d
in
g
o
f
o
u
r
p
r
o
ce
s
s
.
T
h
e
s
u
g
g
ested
m
eth
o
d
-
b
ased
s
teg
a
n
o
g
r
a
p
h
y
v
ar
ies
f
r
o
m
o
th
er
s
teg
an
o
g
r
ap
h
y
a
p
p
r
o
a
ch
es
in
th
at
it
ca
n
h
a
v
e
h
ig
h
p
r
o
tectio
n
wh
ile
r
etain
in
g
im
a
g
e
q
u
ality
at
a
lo
w
co
s
t
an
d
wi
th
a
f
air
p
ay
l
o
ad
.
T
h
e
p
r
esen
t
e
d
wo
r
k
is
id
ea
l
f
o
r
s
ec
u
r
ed
tr
a
n
s
m
is
s
io
n
ap
p
licati
o
n
o
f
v
ar
io
u
s
s
ec
r
et
b
its
,
lik
e
elec
tr
o
n
ic
-
p
atien
t
-
r
ec
o
r
d
s
(
E
P
R
)
tr
an
s
m
is
s
io
n
to
th
e
h
ea
lth
ca
r
e
ce
n
te
r
s
,
an
d
p
r
i
v
ate
co
m
m
u
n
icatio
n
th
at
r
e
q
u
e
s
ts
p
r
iv
ac
y
.
Fig
u
r
e
4
s
h
o
ws
a
g
r
ap
h
ic
e
x
p
lan
atio
n
f
o
r
th
e
p
lan
n
e
d
o
u
tlin
e.
Fig
u
r
e
4
.
Ov
e
r
all
f
lo
w
o
f
th
e
p
r
o
p
o
s
ed
s
ch
em
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
ec
u
r
ity
a
n
d
imp
ercep
tib
ilit
y
i
mp
r
o
vin
g
o
f ima
g
e
s
teg
a
n
o
g
r
a
p
h
y
…
(
N
o
o
r
A
lh
u
d
a
F
.
A
b
b
a
s
)
699
T
h
is
m
eth
o
d
is
m
ad
e
u
p
o
f
f
o
u
r
m
ajo
r
s
u
b
-
s
ec
tio
n
wh
ich
co
n
s
is
t:
i
)
im
ag
e
p
r
ep
ar
atio
n
,
in
v
o
lv
in
g
two
p
ar
ts
,
f
ir
s
t p
ar
t r
esp
o
n
s
ib
le
f
o
r
p
ar
titi
o
n
in
g
o
f
a
n
im
ag
e
an
d
t
h
e
s
ec
o
n
d
p
ar
t,
r
esp
o
n
s
ib
le
f
o
r
p
ix
el
s
elec
tio
n
,
ii
)
p
r
ep
ar
atio
n
o
f
s
ec
r
et
d
ata,
in
v
o
lv
in
g
th
e
co
m
p
r
ess
io
n
(
H
u
f
f
m
an
co
d
in
g
)
o
f
s
ec
r
et
d
ata
p
r
i
o
r
to
th
e
em
b
ed
d
in
g
s
tag
e
,
iii
)
s
tag
e
th
r
ee
in
clu
d
es
th
e
ad
ap
tiv
e
h
id
in
g
o
f
h
id
d
e
n
d
ata
in
s
id
e
co
v
er
im
ag
es
u
s
in
g
a
d
ata
em
b
ed
d
in
g
alg
o
r
ith
m
,
wh
ic
h
allo
ws
th
e
s
teg
o
-
im
ag
e
t
o
b
e
g
en
er
ated
,
iv
)
f
in
ally
,
th
e
s
ec
r
et
-
d
ata
is
r
etr
ie
v
ed
f
r
o
m
th
e
s
teg
o
-
im
ag
e
th
at
h
as
b
ee
n
d
is
tr
ib
u
te
d
at
th
e
r
ec
eiv
in
g
ter
m
in
al
u
s
i
n
g
th
e
ex
tr
ac
tio
n
alg
o
r
ith
m
.
T
h
e
d
ata
co
u
ld
also
b
e
u
s
ed
as a
p
p
r
o
p
r
iate.
All o
f
f
o
u
r
m
ajo
r
s
tag
es a
r
e
s
u
m
m
a
r
izin
g
d
escr
ip
tio
n
as f
o
llo
ws.
3
.
1
.
I
ma
g
e
p
re
pa
ra
t
io
n
I
m
ag
e
p
r
ep
ar
atio
n
co
n
s
is
ts
o
f
two
p
ar
ts
,
f
i
r
s
t
p
ar
t
r
esp
o
n
s
ib
le
f
o
r
p
ar
titi
o
n
i
n
g
o
f
an
im
a
g
e
an
d
th
e
s
ec
o
n
d
p
ar
t,
r
esp
o
n
s
ib
le
f
o
r
p
ix
el
s
elec
tio
n
.
T
h
ese
two
p
ar
ts
at
im
ag
e
p
r
e
p
ar
atio
n
s
tag
e
ar
e
ex
ec
u
ted
s
im
u
ltan
eo
u
s
ly
b
ef
o
r
e
in
tr
o
d
u
cin
g
o
r
ca
n
h
id
in
g
tex
t
in
to
an
im
a
g
e.
T
h
e
co
v
er
im
ag
e
co
n
s
is
ts
o
f
5
1
2
×5
1
2
p
ix
els
co
m
e
f
r
o
m
s
tan
d
ar
d
d
ataset
an
d
th
e
p
ix
el
s
ar
r
an
g
e
d
as
a
m
atr
ix
o
f
tw
o
d
im
en
s
io
n
s
(
2
D
)
,
g
r
o
u
p
in
g
th
ese
p
ix
els
in
to
th
e
b
lo
ck
s
f
o
r
ea
s
y
m
a
n
ag
em
e
n
t.
Selectin
g
o
n
e
b
lo
ck
o
r
g
r
o
u
p
o
f
p
ix
els
f
o
r
em
b
ed
d
in
g
,
t
h
en
s
elec
tin
g
p
i
x
els
in
s
id
e
th
e
b
lo
ck
th
at
n
o
r
m
ally
o
cc
u
r
in
th
is
s
tag
e.
Steg
an
o
g
r
ap
h
y
s
y
s
tem
n
o
r
m
ally
u
s
ed
o
n
e
p
a
r
am
eter
r
an
d
o
m
f
u
n
ctio
n
o
r
o
th
er
alg
o
r
ith
m
lik
e
k
n
i
g
h
t
t
o
u
r
f
o
r
a
r
a
n
d
o
m
p
r
o
ce
s
s
.
T
wo
co
n
tr
o
l p
ar
am
ete
r
s
u
s
ed
in
r
an
d
o
m
p
r
o
ce
s
s
to
ac
h
iev
e
th
e
o
b
jectiv
e
o
f
s
ec
u
r
ity
.
T
wo
p
h
ases
o
f
im
ag
e
d
iv
is
io
n
will p
er
f
o
r
m
;
f
ir
s
t,
p
ar
titi
o
n
in
g
th
e
co
v
er
im
a
g
e
to
6
4
s
u
b
-
s
m
all
im
ag
es c
alled
a
b
lo
c
k
.
Se
lect
th
e
p
ix
els in
s
id
e
th
is
b
lo
ck
th
is
s
elec
tio
n
is
th
e
m
o
s
t im
p
o
r
tan
t
p
r
o
ce
s
s
to
k
ee
p
th
e
s
teg
o
im
ag
e
s
am
e
o
r
ig
in
al
as p
o
s
s
ib
le.
3
.
2
.
H
uf
f
ma
n
c
o
din
g
T
h
e
o
b
jectiv
e
o
f
th
e
H
u
f
f
m
an
co
d
in
g
alg
o
r
ith
m
is
to
d
ec
r
ea
s
e
th
e
s
ize
o
f
tex
t
b
ef
o
r
e
em
b
ed
d
in
g
to
th
e
im
ag
e.
T
h
e
H
u
f
f
m
an
al
g
o
r
i
th
m
d
ep
e
n
d
s
o
n
r
e
d
u
cin
g
th
e
f
r
e
q
u
en
t
letter
s
an
d
g
i
v
es
th
em
p
r
io
r
ity
co
d
e
o
r
s
h
o
r
t
p
ath
in
th
e
Hu
f
f
m
an
tr
ee
.
Hig
h
f
r
eq
u
en
cy
i
n
th
is
ca
s
e
will
g
et
less
p
ath
o
f
v
is
itin
g
to
r
ed
u
ce
g
o
in
g
d
ee
p
ev
e
r
y
tim
e
an
d
let
less
f
r
eq
u
e
n
cy
i
n
d
ee
p
o
f
th
e
tr
ee
,
th
en
will
g
ain
m
an
y
clo
ck
s
in
d
ig
ital
wo
r
d
as
0
,
1
.
Simp
l
y
ca
n
s
u
m
m
ar
ize
th
e
p
r
o
ce
d
u
r
es
o
f
c
o
m
p
r
ess
io
n
tex
t
in
H
u
f
f
m
an
c
o
d
in
g
u
s
ed
with
p
r
o
p
o
s
ed
s
y
s
tem
as
Alg
o
r
ith
m
1
.
Alg
o
r
ith
m
1
.
Hu
f
f
m
a
n
co
d
in
g
Input: array f [1…n] of numerical frequencies or probabilities
Output: binary coding tree with n leaves that has minimum expected code length for f.
Huffman
(f[1….n])
T=empty binary tree
Q=priority queue of pairs (i, f[i], i=1….n, with f as comparison key
For each k=1…n
-
1
i=extract Min(Q)
j=extract Min(Q)
f [n+k]=f[i]+f[j]
insert Node (T, n+k) with children I, j
insert Rear (Q, (n+k), f [n+k]))
Return T
3
.
3
.
E
m
bedd
ing
a
lg
o
rit
hm
(
E
A)
T
h
e
E
A
is
th
e
r
esp
o
n
s
ib
ilit
y
f
o
r
h
i
d
in
g
t
h
e
s
ec
r
ete
m
ess
ag
e
with
in
a
C
I
.
B
y
s
u
p
p
o
r
tin
g
o
f
th
e
s
ec
r
et
-
k
ey
,
th
e
em
b
ed
d
in
g
alg
o
r
ith
m
ca
n
b
e
ab
le
f
o
r
co
n
ce
alin
g
t
h
e
en
cr
y
p
ted
m
ess
ag
e
ad
ap
tiv
ely
in
s
id
e
th
e
L
SB
lay
er
.
I
n
Alg
o
r
ith
m
1
,
th
e
k
e
y
s
tep
s
in
v
o
lv
e
d
in
t
h
e
p
r
esen
ted
em
b
e
d
d
in
g
o
p
e
r
atio
n
a
r
e
illu
s
tr
ated
.
Her
e,
m
ar
k
in
g
ev
er
y
p
ix
el
i
n
to
b
l
o
c
k
m
a
p
is
th
e
m
o
s
t
cr
u
cial
p
r
o
c
ed
u
r
e.
T
h
is
p
r
o
ce
d
u
r
e
is
r
ef
er
r
ed
to
as
em
b
ed
d
in
g
b
lo
ck
.
T
h
e
m
ec
h
an
is
m
s
h
o
w
n
in
Fig
u
r
es
5
p
r
o
v
i
d
es
a
b
e
tter
v
ie
w
o
f
th
e
co
r
e
co
n
ce
p
t
o
f
th
e
s
u
g
g
ested
em
b
ed
d
in
g
alg
o
r
ith
m
.
Alg
o
r
ith
m
2
.
E
m
b
e
d
d
in
g
alg
o
r
ith
m
Input: Cover image
(
)
, Stego Key
(
)
, Secret data
(
)
.
initialize
=cover image,
=secret data ,
=stego key
Apply Huffman using Algorithm 1 coding on on
to get the compression bit stream
)
Segment the
into groups, each with 16 or 32 bits
Select an appropriate cover image
from dataset of cover images (
)
Generate random
number 1 and arrange it according to HMF
-
a vector
Select one block of (8x8) blocks via HMF
-
a vector
Generate random number 2 and arrange it according to HMF
-
b vector
Select the destination pixel via HMF
-
b vector
Generate EM vector and arrange it related to
Odd/Even
Mark each pixel with LSB and
group
If Bit matched>Bit mismatched so that Embedded directly to pixel from secret by step 15
Otherwise, an Inverting secret message will be embedded with step 15
Iteration (Loop) I=1:N
Fetch
bits (0
, 1)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
n
t J E
lec
&
C
o
m
p
E
n
g
,
Vo
l.
12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
6
9
4
-
705
700
a.
If
M
CB
S
=0 and Pixel is even, Do no change in 1
-
LSB layers.
b.
If
M
CB
S
=0 and pixel is odd, Do Changes in 2
-
LSB layer via replace 0 to LSB layer
Else if the 2
-
LSB layer is full, Do Changes in 1
-
LSB layers.
c.
If
M
CB
S
=1 and pixel is odd, Do no change in 1
-
LSB
layers.
d.
If
M
CB
S
=1 and pixel is even, Do changes in 2
-
LSB layer via replace 1 to LSB layer
Else if the 2
-
LSB layer is full, Do Changes in 1
-
LSB layer
I=I+1
Iterate
procedure
16
till
all
the
secret
-
bi
ts
ar
e
hi
dd
en
,
an
d
a
st
eg
o
-
im
ag
e
(S
I)
is
acquired
Output: Stego
-
Image (
I
S
)
Fig
u
r
e
5
.
E
x
am
p
les o
f
em
b
ed
d
in
g
f
o
r
th
e
p
r
o
p
o
s
ed
s
ch
em
e
T
h
e
s
ec
o
n
d
o
b
jectiv
e
wh
ich
t
h
is
s
tu
d
y
s
ee
k
s
to
ac
h
iev
e
th
r
o
u
g
h
th
e
p
r
o
p
o
s
ed
s
ch
em
e,
is
to
h
id
e
th
e
s
ec
r
et
d
ata
with
in
an
L
SB
-
lay
er
.
T
h
is
im
p
lies
th
at
in
th
e
L
SB
,
if
p
ix
els
en
d
with
1
,
th
ey
a
r
e
o
d
d
v
alu
e
p
ix
els,
an
d
o
th
er
wis
e,
th
ey
ar
e
ev
e
n
v
alu
ed
p
ix
el.
I
n
th
is
ca
s
e,
em
b
ed
d
in
g
will
in
v
o
lv
e
s
u
b
s
titu
tin
g
s
ec
r
et
b
its
b
ased
o
n
p
i
x
el
(
th
e
s
ec
o
n
d
la
y
er
,
a
s
ec
r
et
b
it
is
r
ep
lace
d
b
y
o
d
d
p
ix
el,
wh
ile
in
t
h
e
f
ir
s
t
-
lay
er
,
th
e
ev
en
p
ix
el
is
u
s
e
d
to
r
ep
lace
th
e
s
ec
r
et
b
it).
3
.
4
.
Ret
rie
v
ing
a
lg
o
ri
t
hm
T
h
e
r
etr
iev
in
g
o
f
t
h
e
co
n
ce
al
ed
s
ec
r
et
in
f
o
r
m
atio
n
ab
o
u
t
t
h
e
s
teg
o
-
im
ag
e
is
ca
r
r
ied
o
u
t
u
tili
ze
th
e
r
etr
iev
in
g
alg
o
r
ith
m
.
Fo
r
th
e
s
ec
r
et
d
ata
to
b
e
r
etr
iev
ed
s
u
cc
e
s
s
f
u
lly
,
d
if
f
er
e
n
t
p
ar
am
eter
s
a
r
e
u
tili
ze
d
.
So
m
e
o
f
th
ese
p
ar
am
eter
s
in
clu
d
e
H
u
f
f
m
an
co
d
i
n
g
,
Hen
o
n
m
ap
f
u
n
ctio
n
(
HM
F),
an
d
s
teg
o
-
k
ey
s
o
f
d
ata
em
b
e
d
d
e
d
s
ch
em
e.
T
h
e
s
ec
u
r
ity
f
ea
t
u
r
e
o
f
a
p
r
o
p
o
s
in
g
f
r
am
ewo
r
k
is
co
m
p
lem
en
ted
b
y
th
ese
p
ar
a
m
eter
s
,
th
er
eb
y
m
ak
i
n
g
it
d
if
f
icu
lt
f
o
r
attac
k
er
s
e
x
tr
ac
t
s
ec
r
et
d
ata.
T
h
e
k
ey
s
tep
s
in
v
o
lv
ed
in
th
e
p
r
o
p
o
s
ed
m
ec
h
a
n
is
m
o
f
ex
t
r
ac
tio
n
ar
e
p
r
esen
ted
in
Alg
o
r
ith
m
3
.
Alg
o
r
ith
m
3
.
R
etr
iev
in
g
alg
o
r
i
th
m
Input: stego image (
)
, stego key (
)
Begin
=Stego
-
Image,
=Secret
-
Key
Apply random number 1 using HMF
-
a vector
Select one block of 64 blocks HMF
-
a vector
Apply random
number 2 using HMF
-
b vector
Select the stego pixel from HMF
-
b vector
Apply EM vector and arrange it based on odd/even
Mark the LSB of all pixels
Loop start from I=1
:
N
Reverse the step 15 of embedding process from algorithm 1
Repeat step 9 until extract all
secret bits from stego image
Decompression from the resulting bits of step 10 using algorithm1
Re
-
construct the inventive data from the realized bits
Output: secret message (
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
E
n
g
I
SS
N:
2088
-
8
7
0
8
S
ec
u
r
ity
a
n
d
imp
ercep
tib
ilit
y
i
mp
r
o
vin
g
o
f ima
g
e
s
teg
a
n
o
g
r
a
p
h
y
…
(
N
o
o
r
A
lh
u
d
a
F
.
A
b
b
a
s
)
701
4.
E
XP
E
R
I
M
E
N
T
A
L
RE
SUL
T
S AN
D
D
I
SC
USS
I
O
N
Fo
r
p
er
f
o
r
m
i
n
g
t
h
e
ex
p
er
im
en
ts
at
th
is
p
ap
er
,
a
MA
T
L
AB
to
o
l
to
g
eth
e
r
with
eig
h
t
s
tan
d
ar
d
g
r
ay
s
ca
le
im
ag
es wh
ich
ar
e
s
h
o
wn
i
n
Fig
u
r
e
6
was u
tili
ze
d
f
o
r
im
a
g
es with
(
5
1
2
x
5
1
2
)
s
ize
wer
e
o
b
t
ain
ed
.
T
h
e
d
if
f
er
e
n
t
s
teg
o
-
im
ag
es
o
f
o
u
r
s
ch
em
e
at
E
P=2
s
h
o
wn
in
Fig
u
r
e
6
.
Ma
n
y
p
a
r
am
eter
s
wer
e
u
s
ed
i
n
th
e
p
r
o
p
o
s
ed
s
ch
em
e
u
s
in
g
s
u
ch
as PSNR
,
bpp
,
em
b
ed
d
in
g
ca
p
ac
ity
(
EC
)
b
ee
n
e
v
alu
ated
.
L
en
a
L
ig
h
th
o
u
s
e
Pep
p
er
B
ab
o
o
n
Z
eld
a
Ho
u
s
e
C
o
u
p
le
B
o
at
Fig
u
r
e
6
.
C
o
v
e
r
im
ag
es u
s
ed
i
n
th
e
p
r
o
p
o
s
ed
s
ch
e
m
e
4
.
1
.
B
enchm
a
rk
ing
cr
ea
t
ed
o
n E
C,
P
SNR
,
a
nd
bpp
T
h
e
em
b
ed
d
in
g
ca
p
ac
ity
E
C
ca
n
b
e
co
n
s
id
er
e
d
as
th
e
r
atio
o
f
m
ess
ag
e
b
its
n
u
m
b
e
r
to
c
o
v
er
p
ix
els
n
u
m
b
er
[
2
6
]
,
[
2
7
]
,
an
d
b
e
d
ir
e
ctly
ass
o
ciate
d
with
th
e
p
i
x
els
n
u
m
b
er
u
til
ized
i
n
th
e
s
u
g
g
ested
s
ch
em
e
h
er
e
as
a
v
ar
io
u
s
n
u
m
b
er
s
o
f
m
ess
ag
e
b
its
th
at
ca
n
em
b
ed
b
y
o
n
e
p
ix
el.
=
ℎ
ℎ
′
(
2
)
T
h
e
d
iv
er
s
e
p
ay
lo
a
d
ca
p
ac
ities
h
av
e
b
ee
n
u
s
ed
in
th
is
ca
lcu
lat
io
n
,
an
d
o
f
f
er
ed
lik
e
p
e
r
ce
n
tag
e
with
th
e
in
ten
tio
n
o
f
b
ein
g
in
ag
r
ee
m
en
t
with
a
m
o
s
t
r
ec
en
t
s
tu
d
y
n
o
w.
I
n
ten
d
ed
f
o
r
m
o
r
e
e
x
p
lan
atio
n
,
s
o
m
e
in
f
o
r
m
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I
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2
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8
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I
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t J E
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&
C
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p
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g
,
Vo
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12
,
No
.
1
,
Feb
r
u
ar
y
20
22
:
6
9
4
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705
702
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I
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Evaluation Warning : The document was created with Spire.PDF for Python.