T
E
L
K
O
M
N
I
K
A
T
elec
o
m
m
un
ica
t
io
n,
Co
m
pu
t
ing
,
E
lect
ro
nics
a
nd
Co
ntr
o
l
Vo
l.
18
,
No
.
6
,
Dec
em
b
er
2
0
2
0
,
p
p
.
2
9
9
2
~
2
9
9
8
I
SS
N:
1
6
9
3
-
6
9
3
0
,
ac
cr
ed
ited
First Gr
ad
e
b
y
Kem
en
r
is
tek
d
i
k
ti,
Dec
r
ee
No
: 2
1
/E/KPT
/2
0
1
8
DOI
:
1
0
.
1
2
9
2
8
/TE
L
KOM
NI
K
A.
v
1
8
i6
.
1
4
3
4
0
2992
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//jo
u
r
n
a
l.u
a
d
.
a
c.
id
/in
d
ex
.
p
h
p
/TELK
OM
N
I
K
A
The qua
lity o
f
im
a
g
e encr
y
ption t
e
chniques by
reas
o
ned log
ic
M
a
rwa
h K
a
m
il H
us
s
ein
1
,
K
a
re
em
Ra
dh
i H
a
s
s
a
n
2
,
H
a
ider
M
.
Al
-
M
a
s
h
ha
di
3
1,
3
De
p
a
rtme
n
t
o
f
I
n
f
o
rm
a
ti
o
n
S
y
st
e
m
s,
Un
iv
e
rsity
o
f
Ba
sra
,
Ira
q
2
De
p
a
rtme
n
t
o
f
Co
m
p
u
ter
S
c
i
e
n
c
e
,
Un
iv
e
rsit
y
o
f
Ba
sra
,
Ira
q
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Oct
1
7
,
2
0
1
9
R
ev
is
ed
Ma
r
1
7
,
2
0
2
0
Acc
ep
ted
Ma
r
2
7
,
2
0
2
0
On
e
fo
rm
o
f
d
a
ta
is
d
i
g
it
a
l
ima
g
e
s,
b
e
c
a
u
se
o
f
th
e
ir
wi
d
e
sp
re
a
d
o
f
fre
q
u
e
n
t
e
x
c
h
a
n
g
e
o
v
e
r
th
e
In
ter
n
e
t
it
is
n
e
c
e
ss
a
ry
to
p
re
se
rv
e
th
e
se
c
u
rit
y
a
n
d
p
ri
v
a
c
y
o
f
th
e
ima
g
e
s
tran
sm
it
ted
.
Th
e
re
a
re
m
a
n
y
ima
g
e
e
n
c
ry
p
ti
o
n
tec
h
n
iq
u
e
s
th
a
t
h
a
v
e
d
iffere
n
t
se
c
u
rit
y
lev
e
ls
a
n
d
th
e
re
a
re
m
a
n
y
sta
n
d
a
r
d
s
a
n
d
p
r
o
to
c
o
ls
f
o
r
tes
ti
n
g
th
e
q
u
a
l
it
y
o
f
e
n
c
ry
p
ti
o
n
se
c
u
rit
y
.
Th
e
c
ip
h
e
r
i
m
a
g
e
s
c
a
n
b
e
e
v
a
lu
a
te
d
u
sin
g
v
a
ri
o
u
s
q
u
a
li
t
y
m
e
a
su
rin
g
c
rit
e
ria,
th
e
se
m
e
a
su
re
s
q
u
a
n
ti
fy
c
e
rtain
fe
a
tu
re
s o
f
th
e
ima
g
e
.
If
th
e
re
a
re
m
a
n
y
m
e
th
o
d
s t
h
a
t
c
a
n
b
e
a
p
p
li
e
d
to
se
c
u
re
ima
g
e
s;
th
e
q
u
e
sti
o
n
is
wh
a
t
is
t
h
e
m
o
st
p
o
we
rfu
l
sc
h
e
m
e
th
a
t
c
a
n
b
e
u
se
d
a
m
o
n
g
th
e
se
m
e
th
o
d
s?
Th
is
re
se
a
rc
h
try
t
o
a
n
sw
e
r
t
h
is
q
u
e
sti
o
n
b
y
ta
k
in
g
t
h
re
e
d
iffere
n
t
e
n
c
ry
p
ti
o
n
m
e
th
o
d
s
(
riv
e
st
c
ip
h
e
r
5
(
RC5
)
,
c
h
a
o
ti
c
a
n
d
p
e
rm
u
tatio
n
)
a
n
d
m
e
a
su
re
th
e
ir
q
u
a
li
ty
u
sin
g
th
e
p
e
e
k
sig
n
a
l
to
n
o
ise
ra
ti
o
(P
S
NR
)
,
c
o
rre
latio
n
,
e
n
tr
o
p
y
,
n
u
m
b
e
r
o
f
p
ix
e
ls
c
h
a
n
g
e
s
ra
te
(
NPCR
)
a
n
d
u
n
if
ied
a
v
e
ra
g
e
c
h
a
n
g
i
n
g
in
te
n
sity
(
UA
C
I),
th
e
re
su
l
ts
o
f
th
e
se
c
rit
e
ria
we
re
in
p
u
t
t
o
a
fu
z
z
y
lo
g
ic sy
ste
m
th
a
t
wa
s u
se
d
to
fin
d
t
h
e
b
e
st
o
n
e
a
m
o
n
g
t
h
e
m
.
K
ey
w
o
r
d
s
:
C
o
r
r
elatio
n
E
n
cr
y
p
tio
n
E
n
tr
o
p
y
Fu
zz
y
lo
g
ic
NPC
R
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
:
Haid
er
M.
Al
-
Ma
s
h
h
ad
i
,
Dep
ar
tm
en
t o
f
I
n
f
o
r
m
atio
n
Sy
s
tem
s
,
C
o
lleg
e
o
f
C
o
m
p
u
ter
S
cien
ce
an
d
I
n
f
o
r
m
atio
n
T
ec
h
n
o
lo
g
y
,
Un
iv
er
s
ity
o
f
B
asra
,
Gar
m
at
Ali,
B
asra
,
I
r
aq
.
E
m
ail:
m
ash
h
ad
0
1
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
q
u
ality
ass
ess
m
en
t
is
a
v
er
y
im
p
o
r
tan
t
to
o
l
i
n
o
r
d
er
to
c
h
ec
k
th
e
ef
f
icien
cy
a
n
d
ef
f
ec
tiv
en
ess
o
f
th
e
cr
y
p
to
g
r
ap
h
ic
alg
o
r
ith
m
s
.
T
h
er
e
ar
e
s
ev
er
al
m
eth
o
d
s
in
o
r
d
er
to
ass
ess
th
e
cr
y
p
to
g
r
a
p
h
y
tech
n
iq
u
es
i.e
.
d
ep
en
d
i
n
g
o
n
th
e
k
ey
len
g
t
h
,
th
e
b
lo
ck
o
r
wo
r
d
len
g
t
h
,
n
u
m
b
er
o
f
th
e
r
o
u
n
d
s
,
th
e
ex
ec
u
tio
n
tim
e
an
d
s
o
o
n
.
T
ec
h
n
iq
u
es
o
f
th
e
im
a
g
e
en
cr
y
p
tio
n
ar
e
wid
ely
u
s
ed
to
e
n
s
u
r
e
th
at
th
e
s
ec
u
r
e
tr
an
s
m
is
s
io
n
f
o
r
th
e
im
ag
e.
I
m
a
g
e
q
u
ality
ass
ess
m
en
t
(
I
QA)
ca
n
b
e
d
iv
id
ed
i
n
to
two
ty
p
es;
th
e
f
ir
s
t
is
s
u
b
jectiv
e
m
eth
o
d
,
wh
ich
d
ep
en
d
s
o
n
h
u
m
a
n
b
ein
g
s
th
at
ass
ess
th
e
q
u
ality
o
f
th
e
im
ag
e.
W
h
ile
th
e
s
ec
o
n
d
m
eth
o
d
o
f
I
QA
is
th
e
o
b
jectiv
e
m
eth
o
d
s
wh
ich
ca
n
b
e
ass
ess
a
q
u
ality
o
f
th
e
im
ag
e
au
to
m
atica
lly
b
y
u
s
in
g
s
ev
er
al
cr
iter
ia
[
1
-
1
0
]
.
T
h
ese
cr
iter
ia
ar
e
wid
ely
u
s
ed
in
o
r
d
er
to
ev
al
u
ate
th
e
i
m
ag
e
q
u
ality
.
T
h
e
m
ajo
r
id
ea
b
eh
in
d
th
is
p
a
p
er
ca
n
b
e
d
iv
i
d
in
g
in
to
th
r
ee
s
tag
es:
-
Stag
e
1
:
s
elec
t
th
e
im
ag
e
in
o
r
d
er
t
o
en
cr
y
p
t
it
b
y
u
s
in
g
th
r
ee
en
cr
y
p
tio
n
tech
n
iq
u
es
wh
ich
ar
e
(
r
iv
est
cip
h
er
5
(
RC5
)
[
1
1
]
,
c
h
ao
tic
[
1
2
]
an
d
p
er
m
u
tatio
n
[
1
3
]
)
.
-
Stag
e
2
:
Usi
n
g
t
h
e
f
o
llo
win
g
m
etr
ics
o
f
t
h
e
im
ag
e
en
c
r
y
p
ti
o
n
q
u
ality
:
p
ee
k
s
ig
n
al
to
n
o
i
s
e
r
atio
(
PS
NR
)
[
1
4
]
,
co
r
r
elatio
n
[
1
5
]
,
en
t
r
o
p
y
[
1
6
]
,
n
u
m
b
er
o
f
p
ix
els
ch
an
g
es
r
ate
(
NP
C
R
)
an
d
u
n
if
ied
av
er
ag
e
ch
an
g
i
n
g
in
ten
s
ity
(
UACI)
[
1
7
,
1
8
]
.
T
o
m
ea
s
u
r
e
t
h
e
en
c
r
y
p
te
d
im
ag
e
q
u
ality
wh
ich
r
esu
lts
f
r
o
m
s
tag
e
1
;
th
e
r
esu
lt
was f
if
teen
v
alu
es,
f
iv
e
v
alu
es f
o
r
ea
c
h
en
cr
y
p
tio
n
m
eth
o
d
.
-
Stag
e
3
:
f
in
ally
,
u
s
in
g
th
e
f
iv
e
v
alu
es
o
f
q
u
ality
r
esu
lted
f
r
o
m
s
tag
e
2
as
in
p
u
t
to
th
e
f
u
zz
y
lo
g
ic
s
y
s
tem
(
FLS)
,
in
o
r
d
er
to
ass
ess
a
q
u
ality
o
f
ea
c
h
e
n
cr
y
p
ti
o
n
tec
h
n
iq
u
es.
T
h
e
lo
w
r
esu
lt
o
f
FLS
r
ef
er
s
to
th
e
b
est
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
T
h
e
q
u
a
lity o
f ima
g
e
en
cryp
tio
n
tech
n
iq
u
es b
y
r
ea
s
o
n
ed
l
o
g
i
c
(
Ma
r
w
a
h
K
a
mil
Hu
s
s
ein
)
2993
en
cr
y
p
tio
n
m
et
h
o
d
.
B
y
f
ar
,
n
o
s
u
ch
wo
r
k
in
th
e
f
ield
o
f
q
u
ality
ass
ess
m
en
t
f
o
r
im
ag
e
en
cr
y
p
tio
n
tech
n
i
q
u
es
b
y
u
s
in
g
t
h
e
f
u
zz
y
lo
g
ic
s
y
s
te
m
.
Fig
u
r
e
1
s
h
o
ws
th
e
p
r
o
p
o
s
ed
m
eth
o
d
s
tr
u
ctu
r
e,
th
e
im
ag
e
i
s
en
ter
ed
to
th
e
en
cr
y
p
tio
n
m
eth
o
d
lik
e
(
R
C
5
)
in
o
r
d
er
to
p
r
o
d
u
ce
a
cip
h
er
im
ag
e,
af
ter
th
at,
th
e
c
ip
h
er
im
ag
e
will
in
p
u
t
to
th
e
q
u
ality
an
aly
s
is
m
etr
ics
to
ev
alu
ate
t
h
e
m
eth
o
d
e
f
f
icie
n
cy
,
r
esu
lts
o
f
th
e
q
u
ality
an
al
y
s
is
ar
e
en
ter
in
g
to
t
h
e
FLS
to
p
r
o
d
u
ce
t
h
e
v
al
u
e
f
r
o
m
FLS
d
ep
e
n
d
in
g
o
n
th
e
p
r
ev
io
u
s
r
esu
lts
o
f
th
e
q
u
alit
y
an
aly
s
is
.
T
h
is
ap
p
r
o
ac
h
ap
p
lied
f
o
r
o
th
er
two
m
eth
o
d
s
(
ch
a
o
tic
an
d
p
er
m
u
ta
tio
n
)
in
o
r
d
er
to
d
ete
r
m
in
e
th
e
b
est
m
eth
o
d
d
ep
e
n
d
in
g
o
n
th
e
f
u
zz
y
lo
g
ic
s
y
s
tem
v
alu
e.
T
h
is
p
ap
er
was
o
r
g
a
n
iz
ed
as
f
o
llo
ws.
Sectio
n
2
d
escr
i
b
es
th
e
f
u
n
d
am
e
n
tals
o
f
t
h
e
im
ag
e
q
u
ality
cr
iter
ia.
W
h
ile,
s
ec
tio
n
3
d
esc
r
ib
es
th
e
f
u
zz
y
lo
g
ic.
Sectio
n
4
d
i
s
cu
s
s
es
th
e
n
ew
s
ch
em
e
f
o
r
q
u
ality
an
aly
s
is
o
f
en
cr
y
p
tio
n
im
ag
e
m
eth
o
d
s
b
y
u
s
in
g
th
e
f
u
zz
y
lo
g
ic
tech
n
iq
u
e.
T
h
e
e
x
p
er
im
e
n
tal
r
esu
lts
o
f
th
e
n
ew
tech
n
iq
u
es
wer
e
p
r
esen
ted
in
s
ec
tio
n
5
.
Fi
n
ally
,
th
e
co
n
clu
s
io
n
s
wer
e
p
r
esen
t
ed
in
s
ec
tio
n
6
.
Fig
u
r
e
1
.
T
h
e
s
tr
u
ctu
r
e
o
f
th
e
q
u
ality
ass
ess
m
en
t f
o
r
im
a
g
e
e
n
cr
y
p
tio
n
m
eth
o
d
s
u
s
in
g
FLS
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
r
esear
ch
p
r
esen
t
im
ag
e
q
u
ality
ev
alu
atio
n
m
eth
o
d
b
y
ex
p
lo
te
th
e
class
ical
m
eth
o
d
s
(
PS
NR
,
co
r
r
elatio
n
,
en
tr
o
p
y
,
NPC
R
an
d
UACI
)
with
a
n
a
r
tific
ial
in
tellig
en
t
m
eth
o
d
s
i.e
.
co
m
b
in
e
th
e
o
r
d
in
ar
y
im
a
g
e
ev
alu
atio
n
m
eth
o
d
s
with
th
e
f
u
zz
y
lo
g
ic
s
y
s
tem
.
2
.
1
.
P
SNR
PS
NR
is
a
cr
iter
io
n
th
at
u
s
ed
in
o
r
d
e
r
to
m
ea
s
u
r
e
th
e
q
u
ality
d
if
f
er
en
ce
b
etwe
en
th
e
r
esu
lt
ed
im
ag
es
f
r
o
m
th
e
co
m
p
r
ess
io
n
o
r
th
e
e
n
cr
y
p
tio
n
,
b
ased
o
n
t
h
e
o
r
ig
in
a
l
im
ag
e.
PS
NR
wh
ich
d
ep
en
d
s
o
n
th
e
m
ea
n
s
q
u
a
r
e
er
r
o
r
(
MSE
)
ca
n
b
e
ca
lcu
lated
f
r
o
m
(
1
)
[
1
9
,
2
0
]
.
(
1
)
MSE
ca
lcu
lates a
n
av
er
ag
e
o
f
th
e
er
r
o
r
b
etwe
en
th
e
o
r
ig
in
al
im
ag
e
an
d
t
h
e
ex
tr
ac
ted
im
ag
e
.
PS
NR
ca
n
b
e
ca
lcu
lated
as sh
o
wn
in
(
2
)
[
2
1
,
2
2
]
.
(
2
)
T
h
e
b
est v
alu
e
f
o
r
PS
NR
is
n
ea
r
to
ze
r
o
.
2
.
2
.
Co
re
l
a
t
io
n
C
o
r
r
elatio
n
is
th
e
q
u
ality
an
aly
s
is
th
at
u
s
ed
in
o
r
d
er
to
m
ea
s
u
r
e
th
e
s
im
ilar
ity
b
etwe
en
th
e
p
l
ain
im
ag
e
an
d
th
e
cip
h
er
im
ag
e
.
T
h
e
c
o
r
r
elatio
n
ca
n
b
e
ca
lc
u
lated
f
r
o
m
(
3
)
.
C
or
r
=
∑
∑
(
1
(
,
)
−
Ī
1
)
(
2
(
,
)
−
Ī
2
)
=
1
=
1
√
[
∑
∑
(
1
(
,
)
−
Ī
1
)
2
]
[
∑
∑
(
2
(
,
)
−
Ī
2
)
=
1
=
1
2
]
=
1
=
1
(
3
)
T
h
e
b
est p
r
ef
e
r
r
ed
c
o
r
r
elatio
n
v
alu
e
is
n
ea
r
ze
r
o
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
18
,
No
.
6
,
Dec
em
b
e
r
2
0
2
0
:
2
9
9
2
-
299
8
2994
2.3.
E
ntr
op
y
E
n
tr
o
p
y
is
th
e
ex
p
ec
ted
v
alu
e
(
o
r
av
er
a
g
e
o
f
in
f
o
r
m
atio
n
)
wh
ich
ca
n
b
e
ex
tr
ac
ted
f
r
o
m
th
e
m
ess
ag
e.
T
h
e
en
tr
o
p
y
r
ep
r
esen
t
th
e
r
atio
o
r
th
e
q
u
an
tity
o
f
in
f
o
r
m
atio
n
th
et
ex
is
t
in
th
e
im
ag
e,
o
r
h
o
w
m
u
ch
in
f
o
r
m
atio
n
ca
n
b
e
ex
tr
ac
te
d
f
r
o
m
th
e
im
a
g
e.
I
t c
an
b
e
ex
p
r
ess
ed
b
y
u
s
in
g
(
4
)
.
(
4
)
2.4. N
PC
R
and
U
A
C
I NP
C
R
NPC
R
an
d
UACI
N
PC
R
d
et
er
m
in
es
th
e
n
u
m
b
e
r
o
f
th
e
p
ix
els
wh
ich
th
eir
v
alu
es
ch
an
g
e
d
u
r
i
n
g
th
e
o
p
er
atio
n
o
f
en
c
r
y
p
tio
n
,
wh
ile,
UACI
d
eter
m
in
es
th
e
r
atio
o
f
th
e
ch
a
n
g
es
b
etwe
en
two
cip
h
er
-
im
ag
es.
T
h
e
s
ca
le
o
f
NPC
R
i
s
[
0
,
1
]
,
th
e
v
alu
e
0
s
h
o
ws
th
at
th
er
e
is
n
o
ch
an
g
e
in
th
e
p
ix
els
o
f
im
a
g
e1
an
d
im
ag
e
2
.
W
h
ile,
v
alu
e
1
s
h
o
ws
th
at
all
p
ix
els
in
im
ag
e2
ar
e
d
if
f
er
e
n
t
f
r
o
m
im
ag
e
1
.
T
h
e
s
ca
le
o
f
UACI
is
[
0
,
1
]
,
wh
ich
th
e
m
o
s
t p
r
ef
e
r
r
ed
v
alu
e
is
n
e
ar
to
ze
r
o
[
2
3
,
2
4
]
.
3.
F
UZ
Z
Y
L
O
G
I
C
Fu
zz
y
lo
g
ic
s
y
s
tem
h
as
b
ee
n
ad
o
p
ted
in
o
r
d
er
to
s
o
lv
e
m
an
y
p
r
o
b
lem
s
.
FLS
co
n
s
is
ts
f
r
o
m
f
o
u
r
s
tag
es
wh
ich
ar
e
f
u
zz
if
icatio
n
,
i
n
f
er
e
n
ce
en
g
in
e
,
r
u
le
b
ase
an
d
d
ef
u
zz
if
icatio
n
as d
ep
icted
in
F
ig
u
r
e
2
[
2
5
]
.
T
h
er
e
ar
e
m
an
y
ty
p
es o
f
FLS m
o
d
els lik
e
Ma
m
d
an
i a
n
d
T
ak
a
g
i
-
Su
g
en
o
-
Kan
g
(
T
SK
)
m
o
d
el
[
2
6
,
2
7
]
.
Fig
u
r
e
2
.
T
h
e
f
u
zz
y
s
y
s
tem
4.
Q
UALI
T
Y
E
VAL
UAT
I
O
N
USI
NG
F
L
S
T
h
e
p
r
o
p
o
s
e
d
t
e
c
h
n
i
q
u
e
is
u
s
i
n
g
t
h
r
e
e
t
e
c
h
n
i
q
u
e
s
w
h
i
c
h
a
r
e
(
R
C
5
,
c
h
a
o
t
i
c
a
n
d
p
e
r
m
u
t
at
i
o
n
)
i
n
o
r
d
e
r
t
o
e
v
a
l
u
a
t
e
w
h
ic
h
o
f
t
h
e
t
h
r
e
e
e
n
cr
y
p
t
i
o
n
a
l
g
o
r
i
t
h
m
s
is
t
h
e
m
o
r
e
e
f
f
e
c
t
i
v
e
t
h
a
n
o
t
h
e
r
s
,
b
y
u
s
i
n
g
th
e
f
o
l
l
o
w
i
n
g
s
te
p
s
:
-
Select
th
r
e
im
ag
e
to
en
c
r
y
p
t it
b
y
u
s
i
n
g
R
C
5
,
ch
a
o
tic
an
d
p
er
m
u
tatio
n
m
eth
o
d
s
.
-
T
h
e
r
esu
lted
im
ag
e
is
ev
alu
at
ed
b
y
u
s
in
g
th
e
f
iv
e
q
u
ality
an
aly
s
is
cr
iter
ia
(
PS
NR
,
co
r
r
elatio
n
,
en
tr
o
p
y
,
NPC
R
,
UACI)
.
3
.
E
n
ter
th
e
q
u
ality
an
aly
s
is
v
alu
e
wh
ich
r
e
s
u
lted
f
r
o
m
s
tep
to
t
h
e
f
u
zz
y
f
icatio
n
s
tep
o
f
th
e
FLS.
-
C
alcu
late
th
e
o
u
tp
u
t
v
alu
e
o
f
th
e
r
u
le
b
ases
b
y
m
ap
p
in
g
th
e
(
PS
NR
,
co
r
r
elatio
n
,
en
tr
o
p
y
,
NPC
R
,
UA
C
I
)
v
alu
es to
th
e
co
r
r
esp
o
n
d
in
g
f
u
zz
y
s
ets.
-
C
alcu
late
th
e
cr
is
p
o
u
tp
u
t
v
alu
e
u
s
in
g
(
5
)
a
n
d
(
6
)
.
E
x
ec
u
te
th
e
p
r
ev
io
u
s
s
tep
s
f
o
r
o
th
er
m
eth
o
d
s
(
p
er
m
u
tatio
n
an
d
ch
a
o
tic)
.
Select
th
e
b
est m
eth
o
d
d
e
p
en
d
i
n
g
o
n
th
e
lo
w
c
r
is
p
o
u
tp
u
t v
al
u
e.
T
h
e
f
u
zz
y
r
u
le
th
at
im
p
lied
is
th
e
Ma
m
d
an
i
ty
p
e
r
u
le
with
f
iv
e
v
a
lu
es
o
f
th
e
i
n
p
u
t
(
PS
NR
,
co
r
r
elatio
n
,
en
tr
o
p
y
,
NPC
R
an
d
UACI)
in
o
r
d
er
to
p
r
o
d
u
ce
o
n
e
v
alu
e
as
an
o
u
t
p
u
t
wh
ic
h
r
e
p
r
esen
ts
th
e
o
p
tim
al
v
alu
e
f
o
r
th
e
q
u
ality
o
f
th
e
en
cr
y
p
tio
n
m
eth
o
d
.
Fig
u
r
e
3
r
e
p
r
esen
ts
th
e
s
tr
u
ctu
r
e
o
f
FLS
with
th
e
f
iv
e
in
p
u
ts
an
d
o
n
e
o
u
tp
u
t
a
n
d
Fig
u
r
e
4
r
e
p
r
esen
t
s
th
e
tr
ian
g
le
m
em
b
er
s
h
ip
f
u
n
ctio
n
wh
ich
is
u
s
ed
in
t
h
is
ap
p
r
o
ac
h
.
T
h
e
tr
ian
g
le
m
em
b
er
s
h
ip
f
u
n
ctio
n
ca
n
b
e
c
alcu
lated
b
y
u
s
in
g
(
5
)
.
(
5
)
I
n
t
h
e
q
u
a
l
i
t
y
a
s
s
e
s
s
m
e
n
t
F
L
S
,
t
h
e
i
n
p
u
t
v
a
l
u
e
s
a
r
e
p
r
o
c
e
s
s
e
d
b
y
u
s
i
n
g
t
h
e
i
n
f
e
r
e
n
c
e
e
n
g
i
n
e
,
T
a
b
l
e
1
s
h
o
w
s
t
h
e
f
u
z
z
y
r
u
l
e
s
w
h
i
c
h
a
r
e
u
s
e
d
i
n
F
L
S
,
t
h
e
t
o
t
a
l
n
u
m
b
e
r
o
f
f
u
z
z
y
r
u
l
e
b
a
s
e
i
s
3
^
5
=
2
4
3
.
F
o
r
e
x
a
m
p
l
e
,
i
f
P
S
N
R
i
s
l
o
w
,
c
o
r
r
e
l
a
t
i
o
n
i
s
l
o
w
,
e
n
t
r
o
p
y
i
s
l
o
w
,
N
P
C
R
i
s
h
i
g
h
a
n
d
U
A
C
I
i
s
l
o
w
,
t
h
e
o
p
t
i
m
a
l
v
a
l
u
e
(
o
u
t
p
u
t
)
i
s
h
i
g
h
.
T
h
e
r
u
l
e
s
r
u
n
i
n
t
h
e
i
n
f
e
r
e
n
c
e
e
n
g
i
n
e
s
i
m
u
l
t
a
n
e
o
u
s
l
y
.
F
i
n
a
l
l
y
,
d
e
f
u
z
z
i
f
i
c
a
t
i
o
n
s
t
a
g
e
f
i
n
d
s
t
h
a
t
t
h
e
o
p
t
i
m
a
l
c
r
i
s
p
v
a
l
u
e
r
e
p
r
e
s
e
n
t
s
t
h
e
o
u
t
p
u
t
f
r
o
m
t
h
e
f
u
z
z
y
s
p
a
c
e
.
T
h
i
s
v
a
l
u
e
r
e
p
r
e
s
e
n
t
s
t
h
e
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
f
o
r
t
h
e
m
e
t
h
o
d
o
f
e
n
c
r
y
p
t
i
o
n
.
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
T
h
e
q
u
a
lity o
f ima
g
e
en
cryp
tio
n
tech
n
iq
u
es b
y
r
ea
s
o
n
ed
l
o
g
i
c
(
Ma
r
w
a
h
K
a
mil
Hu
s
s
ein
)
2995
Fig
u
r
e
3
.
T
h
e
s
tr
u
ctu
r
e
o
f
FLS
u
s
in
g
f
iv
e
i
n
p
u
ts
an
d
o
n
e
o
u
t
p
u
t o
f
t
h
e
o
p
tim
al
q
u
ality
v
al
u
e
f
o
r
th
e
en
cr
y
p
tio
n
m
eth
o
d
Fig
u
r
e
4
.
R
ep
r
esen
tatio
n
o
f
in
p
u
ts
m
em
b
er
s
h
ip
f
u
n
ctio
n
T
ab
le
1
.
Fu
zz
y
r
u
les o
f
th
e
tec
h
n
iq
u
e
VL
L
M
H
VH
VL
VH
VH
H
M
L
L
VH
H
H
M
L
M
H
H
M
L
VL
H
H
M
M
L
VL
VH
H
M
M
L
VL
Fu
zz
y
s
y
s
tem
ca
n
b
e
e
x
p
r
ess
ed
b
y
u
s
in
g
th
e
f
o
llo
win
g
p
r
o
ce
d
u
r
e:
Pro
ce
d
u
r
e
Fu
zz
y
:
// Pr
o
ce
d
u
r
e
Qu
ality
E
v
alu
atio
n
B
eg
in
Dete
r
m
in
e
n
o
.
o
f
m
e
m
b
er
s
h
ip
f
u
n
ctio
n
f
o
r
.
I
n
p
u
t1
s
u
ch
as PSNR
=3
I
n
p
u
t2
s
u
ch
as C
o
r
r
elatio
n
=
3
I
n
p
u
t3
s
u
ch
as E
n
tr
o
p
y
=
3
I
n
p
u
t4
s
u
ch
as NPSR
=3
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
18
,
No
.
6
,
Dec
em
b
e
r
2
0
2
0
:
2
9
9
2
-
299
8
2996
I
n
p
u
t5
s
u
ch
as UA
C
I
=3
Ou
tp
u
t su
ch
as M
o
=5
I
n
p
u
t th
e
v
alu
es o
f
PS
NR
,
C
o
r
r
,
E
n
t,
NPC
R
,
UACI
f
r
o
m
th
e
s
tatis
t
ical
an
aly
s
is
s
tag
e;
B
eg
in
C
alcu
late
th
e
m
em
b
er
s
h
ip
f
u
n
ctio
n
f
o
r
th
e
PS
NR
,
C
o
r
r
,
E
n
t,
NPC
R
,
UACI,
in
th
e
I
n
p
u
t
1
…I
n
p
u
t5
by
(
5
)
; Pu
t th
e
r
esu
lt in
Y1
.
.
.
Y
5
;
U
K
=
∑
∑
∗
=
2
=
1
=
1
=
1
C
alcu
late
th
e
d
eg
r
ee
o
f
all
f
u
z
zy
s
ets
U
k
by
th
e
eq
u
atio
n
:
Usi
n
g
C
OG
s
tr
ateg
ies to
f
ix
e
d
en
cr
y
p
tio
n
b
lo
c
k
as a
cr
is
p
v
a
lu
e
ac
co
r
d
in
g
to
:
=
∑
∗
=
1
∑
=
1
E
n
d
; E
n
d
;
5.
E
XP
E
R
I
M
E
N
T
A
L
RE
SUL
T
S
I
n
o
r
d
e
r
t
o
e
v
a
l
u
a
t
e
t
h
e
t
e
c
h
n
i
q
u
e
,
t
h
r
e
e
e
n
c
r
y
p
t
i
o
n
a
l
g
o
r
i
t
h
m
s
w
e
r
e
u
s
e
d
(
R
C
5
,
p
e
r
m
u
t
a
t
i
o
n
a
n
d
c
h
a
o
t
i
c
)
.
E
a
c
h
o
n
e
o
f
t
h
e
s
e
m
e
t
h
o
d
s
r
u
n
s
o
n
e
i
g
h
t
d
i
f
f
e
r
e
n
t
s
t
a
n
d
a
r
d
i
m
a
g
e
s
w
h
i
c
h
a
r
e
(
b
i
r
d
s
,
b
o
a
t
,
b
a
r
c
o
,
h
o
u
s
e
,
s
t
a
r
,
p
e
p
p
e
r
s
,
b
o
y
s
a
n
d
f
i
n
g
e
r
p
r
i
n
t
)
.
T
a
b
l
e
2
r
e
p
r
e
s
e
n
t
s
v
a
l
u
e
s
o
f
t
h
e
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
m
e
t
r
i
c
s
t
h
a
t
r
e
s
u
l
t
e
d
f
r
o
m
R
C
5
e
n
c
r
y
p
t
i
o
n
m
e
t
h
o
d
s
f
o
r
e
i
g
h
t
i
m
a
g
e
s
b
y
u
s
i
n
g
f
i
v
e
m
e
t
r
i
c
s
.
T
a
b
l
e
3
r
e
p
r
e
s
e
n
t
s
t
h
e
v
a
l
u
e
s
o
f
F
L
S
w
h
i
c
h
e
v
a
l
u
a
t
e
t
h
e
m
e
t
r
i
c
s
o
f
T
a
b
l
e
2
.
T
a
b
l
e
4
r
e
p
r
e
s
e
n
t
s
t
h
e
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
m
e
t
r
i
c
s
t
h
a
t
r
e
s
u
l
t
e
d
f
r
o
m
c
h
a
o
t
i
c
m
e
t
h
o
d
o
f
e
i
g
h
t
i
m
a
g
e
s
.
T
a
b
l
e
5
r
e
p
r
e
s
e
n
t
s
t
h
e
v
a
l
u
e
s
o
f
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
u
s
i
n
g
F
L
S
w
h
i
c
h
e
v
a
l
u
a
t
e
t
h
e
m
e
t
r
i
c
s
o
f
T
a
b
l
e
4.
T
a
b
l
e
6
,
r
e
p
r
e
s
e
n
t
s
t
h
e
v
a
l
u
e
s
o
f
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
m
e
t
r
i
c
s
r
e
s
u
l
t
e
d
f
r
o
m
t
h
e
p
e
r
m
u
t
a
t
i
o
n
e
n
c
r
y
p
t
i
o
n
m
e
t
h
o
d
s
f
o
r
e
i
g
h
t
i
m
a
g
e
s
.
T
a
b
l
e
7
s
h
o
w
s
t
h
e
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
u
s
i
n
g
f
u
z
z
y
s
y
s
t
e
m
t
h
a
t
r
e
s
u
l
t
e
d
f
r
o
m
t
h
e
m
e
t
r
i
c
s
o
f
t
h
e
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
f
o
r
e
i
g
h
t
i
m
a
g
e
s
.
F
r
o
m
T
a
b
l
e
s
2
,
4
,
a
n
d
6
,
i
t
'
s
v
e
r
y
d
i
f
f
i
c
u
l
t
t
o
d
e
t
e
r
m
i
n
e
w
h
i
c
h
o
n
e
o
f
t
h
r
e
e
m
e
t
h
o
d
s
i
s
t
h
e
b
e
s
t
t
o
e
n
c
r
y
p
t
t
h
e
i
m
a
g
e
,
d
e
p
e
n
d
i
n
g
o
n
t
h
e
o
r
d
i
n
a
r
y
m
e
t
r
i
c
s
(
P
S
N
R
,
c
o
r
r
e
l
a
t
i
o
n
,
e
n
t
r
o
p
y
,
N
P
C
R
a
n
d
U
A
C
I
)
b
e
c
a
u
s
e
t
h
e
v
a
l
u
e
s
o
f
t
h
e
s
e
m
e
t
h
o
d
s
a
r
e
v
e
r
y
s
i
m
i
l
a
r
o
r
v
e
r
y
c
l
o
s
e
r
.
S
o
,
v
a
l
u
e
s
o
f
t
h
e
s
e
m
e
t
r
i
c
s
a
r
e
u
s
i
n
g
a
s
i
n
p
u
t
s
t
o
F
L
S
i
n
o
r
d
e
r
t
o
d
e
t
e
r
m
i
n
e
i
n
p
r
e
c
i
s
e
l
y
w
h
i
c
h
o
n
e
o
f
t
h
e
s
e
m
e
t
h
o
d
s
i
s
b
e
t
t
e
r
t
h
a
n
t
h
e
o
t
h
e
r
.
T
a
b
l
e
s
3
,
4
,
a
n
d
5
s
h
o
w
t
h
e
f
u
z
z
y
l
o
g
i
c
v
a
l
u
e
s
w
h
i
c
h
u
s
e
d
t
o
d
e
t
e
r
m
i
n
e
a
q
u
a
l
i
t
y
a
n
a
l
y
s
i
s
f
o
r
e
a
c
h
e
n
c
r
y
p
t
i
o
n
m
e
t
h
o
d
.
T
ab
le
2
.
Me
tr
ics o
f
q
u
ality
an
aly
s
is
f
o
r
RC
5
en
cr
y
p
tio
n
m
eth
o
d
I
mag
e
N
a
m
e
P
S
N
R
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
C
o
r
r
d
a
t
i
o
n
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
En
t
r
o
p
y
f
o
r
c
i
p
h
e
r
i
ma
g
e
N
P
C
R
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
U
A
C
I
B
i
r
d
s
4
3
.
2
9
4
7
0
.
0
2
7
8
5
4
8
7
.
9
4
9
2
1
0
.
9
9
9
3
0
.
5
7
1
2
9
1
B
o
a
t
4
3
.
4
9
1
7
0
.
0
0
1
6
7
3
2
6
7
.
9
3
3
1
3
1
0
.
4
9
0
3
5
5
H
o
u
s
e
4
3
.
4
0
7
3
0
.
0
2
0
9
0
4
2
7
.
9
4
3
2
9
1
0
.
5
0
2
6
6
9
B
a
r
c
o
4
3
.
4
1
7
2
0
.
0
0
3
2
0
7
5
2
7
.
9
0
8
7
2
1
0
.
6
3
9
4
0
4
B
o
y
s
4
3
.
4
8
0
6
0
.
0
2
5
2
6
6
7
7
.
7
7
5
1
8
1
0
.
5
9
1
2
3
3
S
t
a
r
4
2
.
8
0
2
9
0
.
0
4
5
6
9
4
9
4
.
8
7
6
5
0
.
9
9
9
8
0
.
8
0
1
6
2
4
P
e
p
p
e
r
s
4
3
.
4
0
3
5
0
.
0
2
0
0
2
6
4
7
.
9
5
3
7
3
1
0
.
5
1
6
0
0
7
F
i
n
g
e
r
-
p
r
i
n
t
4
3
.
3
4
1
6
0
.
0
0
0
4
2
4
1
1
1
1
7
.
9
7
2
9
9
9
1
0
.
0
4
4
1
2
5
T
ab
le
3
.
Qu
alit
y
a
n
aly
s
is
u
s
in
g
FLS to
R
C
5
en
cr
y
p
tio
n
m
et
h
o
d
I
mag
e
N
a
m
e
B
i
r
d
s
B
o
a
t
H
o
u
s
e
B
a
r
c
o
B
o
y
s
S
t
a
r
P
e
p
p
e
r
s
F
i
n
g
e
r
-
p
r
i
n
t
F
u
z
z
y
Lo
g
i
c
0
.
2
8
2
2
7
4
0
.
2
5
8
9
8
1
0
.
2
5
8
9
9
1
0
.
3
0
4
1
1
1
0
.
3
0
2
2
5
9
0
.
5
9
4
6
9
8
0
.
4
0
3
4
3
5
0
.
4
7
0
5
2
5
T
ab
le
4
.
Qu
ality
a
n
aly
s
is
m
etr
ics f
o
r
c
h
ao
tic
en
c
r
y
p
tio
n
m
et
h
o
d
I
mag
e
N
a
m
e
P
S
N
R
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
C
o
r
r
d
a
t
i
o
n
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
En
t
r
o
p
y
f
o
r
c
i
p
h
e
r
i
ma
g
e
N
P
C
R
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
U
A
C
I
B
i
r
d
s
1
1
.
8
2
6
3
0
.
0
0
2
6
5
0
3
6
7
.
3
0
4
2
4
0
.
9
9
2
2
1
8
0
.
1
9
6
8
3
7
B
o
a
t
1
1
.
7
6
3
7
7
.
8
1
4
8
7
5
7
.
1
9
0
4
6
0
.
9
9
0
2
6
5
0
.
1
9
5
7
9
9
H
o
u
s
e
1
1
.
6
6
7
7
0
.
0
0
2
3
9
8
7
3
7
.
4
8
3
0
4
0
.
9
9
3
5
9
1
0
.
2
6
8
9
3
4
B
a
r
c
o
9
.
3
8
5
3
5
0
.
0
0
1
0
3
6
2
7
.
3
5
6
1
0
.
9
9
1
2
8
7
0
.
2
6
8
9
3
4
B
o
y
s
1
0
.
5
4
4
7
0
.
0
0
0
3
2
1
3
6
7
.
2
1
7
3
1
0
.
9
8
7
4
7
3
0
.
2
4
0
3
4
8
S
t
a
r
7
.
8
7
9
4
7
0
.
0
0
2
2
1
5
3
3
4
.
1
1
6
2
8
0
.
6
3
9
0
3
8
0
.
2
8
2
1
3
7
P
e
p
p
e
r
s
9
.
6
7
2
2
5
0
.
1
5
9
6
3
7
0
.
0
1
0
4
0
6
6
1
0
.
2
5
7
5
5
9
F
i
n
g
e
r
-
p
r
i
n
t
9
.
9
6
4
5
8
0
.
0
9
5
1
7
4
3
0
.
0
3
0
5
3
2
8
1
0
.
0
2
5
8
1
9
3
Evaluation Warning : The document was created with Spire.PDF for Python.
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
T
h
e
q
u
a
lity o
f ima
g
e
en
cryp
tio
n
tech
n
iq
u
es b
y
r
ea
s
o
n
ed
l
o
g
i
c
(
Ma
r
w
a
h
K
a
mil
Hu
s
s
ein
)
2997
T
ab
le
5
.
Qu
ality
a
n
aly
s
is
b
y
u
s
in
g
FLS to
c
h
ao
tic
en
cr
y
p
tio
n
m
eth
o
d
I
mag
e
N
a
m
e
B
i
r
d
s
B
o
a
t
H
o
u
s
e
B
a
r
c
o
B
o
y
s
S
t
a
r
P
e
p
p
e
r
s
F
i
n
g
e
r
-
p
r
i
n
t
F
u
z
z
y
Lo
g
i
c
0
.
5
8
8
5
6
1
0
.
5
8
8
2
3
2
0
.
5
9
3
5
6
6
0
.
6
2
8
8
1
8
0
.
5
9
5
1
8
6
0
.
6
6
2
5
4
4
0
.
5
9
9
2
2
6
0
.
6
0
0
0
8
7
T
ab
le
6
.
Qu
ality
a
n
aly
s
is
m
etr
ics f
o
r
p
er
m
u
tatio
n
en
c
r
y
p
tio
n
m
eth
o
d
I
mag
e
N
a
m
e
P
S
N
R
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
C
o
r
r
d
a
t
i
o
n
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
En
t
r
o
p
y
f
o
r
c
i
p
h
e
r
i
ma
g
e
N
P
C
R
P
l
a
i
n
i
ma
g
e
v
s
c
i
p
h
e
r
i
m
a
g
e
U
A
C
I
B
i
r
d
s
1
1
.
8
2
6
3
0
.
0
0
2
6
5
0
3
6
7
.
3
0
4
2
4
0
.
9
9
2
2
1
8
0
.
1
9
6
8
3
7
B
o
a
t
1
1
.
7
6
3
7
7
.
8
1
4
8
7
e
-
5
7
.
1
9
0
4
6
0
.
9
9
0
2
6
5
0
.
1
9
5
7
9
9
H
o
u
s
e
1
1
.
6
6
7
7
0
.
0
0
2
3
9
8
7
3
7
.
4
8
3
0
4
0
.
9
9
3
5
9
1
0
.
2
1
0
8
4
1
B
a
r
c
o
9
.
3
8
5
3
5
0
.
0
0
1
0
1
3
6
2
7
.
3
5
6
1
0
.
9
9
1
2
8
7
0
.
2
6
8
9
3
4
B
o
y
s
1
0
.
5
4
4
7
0
.
0
0
0
3
1
2
1
3
6
7
.
2
1
7
3
1
0
.
9
8
7
4
7
3
0
.
2
4
0
3
4
8
S
t
a
r
7
.
8
7
9
4
7
0
.
0
0
2
2
1
5
3
3
4
.
1
1
6
2
8
0
.
6
3
9
0
3
8
0
.
2
8
2
1
3
7
P
e
p
p
e
r
s
1
0
.
6
2
1
7
0
.
0
0
5
1
6
1
3
5
7
.
5
3
2
6
9
0
.
9
9
4
2
1
7
0
.
2
3
9
0
0
1
F
i
n
g
e
r
-
p
r
i
n
t
1
0
.
9
2
5
5
0
.
0
0
3
4
9
3
1
1
6
.
7
3
1
7
1
0
.
9
8
9
9
0
.
2
3
2
2
4
9
T
ab
le
7
.
Qu
ality
a
n
aly
s
is
v
alu
es b
y
u
s
in
g
FLS to
p
e
r
m
u
tatio
n
m
eth
o
d
I
mag
e
N
a
m
e
B
i
r
d
s
B
o
a
t
H
o
u
s
e
B
a
r
c
o
B
o
y
s
S
t
a
r
P
e
p
p
e
r
s
F
i
n
g
e
r
-
p
r
i
n
t
F
u
z
z
y
Lo
g
i
c
0
.
4
0
8
0
7
2
0
.
4
1
2
4
9
5
0
.
3
9
7
2
2
5
0
.
3
8
0
7
9
4
0
.
3
9
5
4
8
0
.
4
1
4
5
7
9
0
.
6
9
5
4
9
4
0
.
4
1
4
5
7
9
6.
CO
NCLU
SI
O
NS
Qu
ality
ass
e
s
s
m
en
t
o
f
th
e
en
cr
y
p
tio
n
m
eth
o
d
s
is
v
er
y
im
p
o
r
tan
t
in
o
r
d
er
to
d
eter
m
in
e
th
e
en
cr
y
p
tio
n
m
ec
h
an
is
m
s
tr
en
g
th
.
Sev
er
a
l
q
u
ality
ass
es
s
m
en
t
m
eth
o
d
s
wh
ich
ar
e
im
p
lem
en
ted
to
d
eter
m
in
e
th
e
cr
y
p
to
g
r
ap
h
ic
m
eth
o
d
ef
f
icien
cy
b
y
u
s
in
g
s
o
m
an
y
m
etr
i
cs.
I
n
t
h
is
w
o
r
k
,
a
n
ew
m
et
h
o
d
o
f
th
e
q
u
ality
ass
es
s
m
en
t h
as b
ee
n
ap
p
lied
o
n
th
r
ee
im
ag
e
e
n
cr
y
p
tio
n
alg
o
r
ith
m
s
wh
ich
ar
e
(
R
C
5
,
ch
ao
tic
an
d
p
er
m
u
tatio
n
)
,
b
y
ca
lcu
latin
g
th
e
q
u
ality
an
al
y
s
is
f
o
r
ea
ch
m
eth
o
d
b
y
u
s
in
g
f
iv
e
m
etr
ics
(
PS
NR
,
en
tr
o
p
y
,
co
r
r
elatio
n
,
NPC
R
an
d
UACI)
,
th
e
r
esu
lts
o
f
th
ese
m
etr
ics
en
ter
to
FLS
in
o
r
d
er
to
d
eter
m
in
e
th
e
f
itn
ess
o
f
ea
ch
m
eth
o
d
o
f
en
cr
y
p
tio
n
.
T
h
e
r
esu
lts
s
h
o
w
th
at
th
e
b
est
m
eth
o
d
was
R
C
5
.
T
h
er
ef
o
r
e,
FL
q
u
ality
ass
ess
m
en
t
f
o
r
th
e
im
ag
e
en
cr
y
p
tio
n
m
eth
o
d
s
ad
d
s
a
n
e
w
m
eth
o
d
i
n
o
r
d
er
to
an
al
y
tical
co
m
p
ar
is
o
n
am
o
n
g
th
e
im
p
lem
en
ted
m
eth
o
d
s
.
As
a
f
u
tu
r
e
wo
r
k
,
e
x
p
lo
r
in
g
m
o
r
e
m
eth
o
d
s
an
d
in
v
esti
g
atin
g
th
e
p
er
f
o
r
m
an
ce
o
f
u
s
in
g
th
e
m
eth
o
d
s
to
ch
ec
k
its
ef
f
ec
tiv
en
ess
b
y
u
s
in
g
FL
s
y
s
tem
.
RE
F
E
R
E
NC
E
S
[1
]
S
h
e
ik
h
H.
R.
,
B
o
v
i
k
A.
C.
,
“
I
m
a
g
e
in
fo
rm
a
ti
o
n
a
n
d
v
isu
a
l
q
u
a
li
ty
,”
IEE
E
T
ra
n
s
a
c
ti
o
n
s
.
on
I
m
a
g
e
Pro
c
e
ss
in
g
,
v
o
l.
1
5
,
n
o
.
2
,
p
p
.
4
3
0
-
4
4
4
,
F
e
b
r
u
a
ry
2
0
0
6
.
[2
]
Yo
u
J.,
e
t
a
l
.
,
“
P
e
rc
e
p
tu
a
l
q
u
a
li
t
y
a
ss
e
ss
m
e
n
t
b
a
se
d
o
n
v
isu
a
l
a
tt
e
n
ti
o
n
a
n
a
ly
sis
,”
Pro
c
e
e
d
in
g
s
o
f
th
e
1
7
t
h
ACM
in
ter
n
a
t
io
n
a
l
c
o
n
fer
e
n
c
e
o
n
M
u
lt
i
m
e
d
ia
,
p
p
.
1
9
-
2
4
,
Oc
t
o
b
e
r
2
0
0
9
.
[3
]
Zh
a
i
G
.
,
Zh
a
n
g
W
.
a
n
d
Li
n
W
.
,
“
LG
P
S
:
P
h
a
se
b
a
se
d
ima
g
e
q
u
a
li
t
y
a
ss
e
ss
m
e
n
t
m
e
tri
c
,”
IEE
E
W
o
rk
sh
o
p
o
n
S
i
g
n
a
l
Pro
c
e
ss
in
g
S
y
ste
m
s
,
p
p
.
6
0
5
-
6
0
9
,
Oc
t
o
b
e
r
2
0
0
7
.
[4
]
Li
u
Z.
a
n
d
Lag
a
n
iere
R.
,
“
On
t
h
e
u
se
o
f
p
h
a
se
c
o
n
g
r
u
e
n
c
y
t
o
e
v
a
lu
a
te
ima
g
e
sim
il
a
rit
y
.”
IEE
E
In
ter
n
a
t
io
n
a
l
Co
n
fer
e
n
c
e
o
n
Aco
u
stics
S
p
e
e
c
h
a
n
d
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
Pr
o
c
e
e
d
in
g
s
,
M
a
y
2
0
0
6
.
[5
]
Da
v
is
L.
S
.
,
W
u
Z.
a
n
d
S
u
n
H.
,
“
C
o
n
t
o
u
r
-
b
a
se
d
m
o
ti
o
n
e
stim
a
ti
o
n
.
”
Co
mp
u
t
er
v
isio
n
,
Gr
a
p
h
ics
,
a
n
d
.
i
ma
g
e
Pro
c
e
ss
,
v
o
l.
2
3
,
n
o
.
3
,
p
p
.
3
1
3
-
3
2
6
,
S
e
p
te
m
b
e
r
1
9
8
3
.
[6
]
Ha
n
S
.
,
M
a
o
H.
a
n
d
Da
ll
y
W.
J.
A
.,
“D
e
e
p
n
e
u
ra
l
n
e
two
r
k
c
o
m
p
re
ss
io
n
p
i
p
e
li
n
e
:
P
r
u
n
in
g
,
q
u
a
n
ti
z
a
ti
o
n
,
h
u
ffm
a
n
e
n
c
o
d
i
n
g
.
”
a
rXiv P
re
p
r
,
F
e
b
ru
a
r
y
2
0
1
6
.
[7
]
F
u
W.
,
G
u
X.
a
n
d
Wan
g
Y.
,
“
Im
a
g
e
q
u
a
li
t
y
a
ss
e
ss
m
e
n
t
u
si
n
g
e
d
g
e
a
n
d
c
o
n
tras
t
sim
il
a
rit
y
.”
IEE
E
I
n
t
e
rn
a
ti
o
n
a
l
J
o
in
t
Co
n
fer
e
n
c
e
o
n
Ne
u
ra
l
Ne
two
rk
s (
IEE
E
W
o
rld
Co
n
g
re
ss
o
n
Co
mp
u
t
a
ti
o
n
a
l
In
tell
ig
e
n
c
e
)
,
p
p
.
8
5
2
-
8
5
5
,
Ju
n
e
2
0
0
8
.
[8
]
Ya
p
V.
V.
,
“
Wav
e
let
-
b
a
se
d
ima
g
e
c
o
m
p
re
ss
io
n
f
o
r
m
o
b
il
e
a
p
p
li
c
a
ti
o
n
s.
”
M
id
d
les
e
x
Un
ive
rs
it
y
.
2
0
0
5
.
[9
]
Ya
n
g
C.
L.
,
Wan
g
F
.
a
n
d
Xia
o
D
.
,
“
Co
n
to
u
rlet
t
ra
n
sfo
rm
-
b
a
se
d
str
u
c
tu
ra
l
sim
il
a
rit
y
f
o
r
ima
g
e
q
u
a
li
t
y
a
ss
e
ss
m
e
n
t.
”
IEE
E
In
ter
n
a
ti
o
n
a
l
C
o
n
fer
e
n
c
e
o
n
In
tell
ig
e
n
t
Co
m
p
u
ti
n
g
a
n
d
I
n
tel
li
g
e
n
t
S
y
ste
ms
,
p
p
.
1
7
5
-
1
7
9
,
N
o
v
e
m
b
e
r
2
0
0
9
.
[1
0
]
Alh
ij
a
j
A.
A.
a
n
d
H
u
ss
e
in
M
.
K.
,
“
S
tere
o
ima
g
e
s
e
n
c
ry
p
ti
o
n
b
y
OSA
&
RS
A
a
l
g
o
r
it
h
m
s
.
”
J
o
u
rn
a
l
Ph
y
s
ics
Co
n
f
e
re
n
c
e
S
e
r
ies
,
v
o
l.
1
2
7
9
,
n
o
.
1
,
p
p
.
1
-
7
,
J
a
n
u
a
ry
.
2
0
1
9
.
[1
1
]
Hu
ss
e
in
M
.
K.
,
Alh
i
jaj
A
,
“
TDL
a
n
d
R
o
n
Ri
v
e
st,
Ad
i
S
h
a
m
ir,
a
n
d
Leo
n
a
rd
Ad
lem
a
n
i
n
S
tere
o
i
m
a
g
e
s
e
n
c
ry
p
t
”
J
o
u
rn
a
l
o
f
A
d
v
a
n
c
e
d
Res
e
a
rc
h
in
Dy
n
a
mic
a
l
a
n
d
Co
n
tro
l
S
y
ste
ms
-
JA
RDCS
,
v
o
l.
1
1
,
n
o
.
0
1
,
p
p
.
1
8
1
1
-
1
8
1
7
,
2
0
1
8.
[1
2
]
S
a
th
ish
k
u
m
a
r
G
.
A.,
Bh
o
o
p
a
t
h
y
K.,
S
iri
a
a
m
N.
,
“
Im
a
g
e
e
n
c
ry
p
ti
o
n
b
a
se
d
o
n
d
iffu
si
o
n
a
n
d
m
u
lt
ip
le
c
h
a
o
ti
c
m
a
p
s
.
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
Ne
tw
o
rk
S
e
c
u
rity &
Its
Ap
p
li
c
a
ti
o
n
s
,
v
o
l.
3
,
n
o
.
2
,
p
p
.
1
8
1
-
1
9
4
,
2
0
1
1
.
[1
3
]
S
e
sh
a
P
.
,
I
n
d
ra
k
a
n
ti
,
A
v
a
d
h
a
n
i
P
.
S
.
,
“
P
e
rm
u
tatio
n
b
a
se
d
Im
a
g
e
e
n
c
ry
p
ti
o
n
tec
h
n
i
q
u
e
.
”
I
n
ter
n
a
t
i
o
n
a
l
J
o
u
rn
a
l
o
f
Co
mp
u
ter
A
p
p
li
c
a
ti
o
n
s
,
v
o
l.
2
8
,
n
o
.
8
,
p
p
.
4
5
-
4
7
,
Au
g
u
st
2
0
1
1
.
[1
4
]
Wan
g
Z.
,
Bo
v
ik
A.
C.
,
S
h
e
i
k
h
H.
D.
a
n
d
S
imo
n
c
e
ll
i
E.
,
“
Im
a
g
e
q
u
a
li
ty
a
ss
e
ss
m
e
n
t:
fro
m
e
rro
r
v
isib
il
it
y
to
str
u
c
tu
ra
l
sim
il
a
rit
y
,”
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Ima
g
e
Pro
c
e
ss
in
g
,
v
o
l.
4
,
n
o
.
4
,
p
p
.
6
0
0
-
6
1
2
,
A
p
ril
2
0
0
4
.
[1
5
]
Xu
e
h
u
Ya
n
,
e
t
a
l.
,
“
A
n
e
w
a
ss
e
ss
m
e
n
t
m
e
a
su
re
o
f
sh
a
d
o
w
ima
g
e
q
u
a
li
ty
b
a
se
d
o
n
e
rro
r
d
iffu
si
o
n
tec
h
n
iq
u
e
s
.
”
J
o
u
rn
a
l
o
f
In
fo
rm
a
t
io
n
Hid
i
n
g
a
n
d
M
u
lt
i
me
d
ia
S
ig
n
a
l
Pro
c
e
ss
in
g
,
v
o
l.
4
,
n
o
.
2
,
p
p
.
1
1
8
-
1
2
6
,
Ja
n
u
a
ry
2
0
1
3
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
1
6
9
3
-
6
9
3
0
T
E
L
KOM
NI
KA
T
elec
o
m
m
u
n
C
o
m
p
u
t E
l Co
n
tr
o
l
,
Vo
l.
18
,
No
.
6
,
Dec
em
b
e
r
2
0
2
0
:
2
9
9
2
-
299
8
2998
[1
6
]
S
h
a
n
n
o
n
C.
E.
,
“
C
o
m
m
u
n
ica
ti
o
n
th
e
o
r
y
o
f
se
c
re
c
y
sy
ste
m
s
.
”’
Bell
S
y
ste
m
T
e
c
h
n
ica
l
J
o
u
rn
a
l
,
v
o
l.
2
8
,
n
o
.
4
,
p
p
.
6
5
6
-
7
1
5
,
Oc
t
o
b
e
r
1
9
4
9
.
[1
7
]
Ch
e
n
G
.
,
M
a
o
Y.
a
n
d
Ch
u
i
C.
A
.,
“
S
y
m
m
e
tri
c
ima
g
e
e
n
c
ry
p
ti
o
n
sc
h
e
m
e
b
a
se
d
o
n
3
D
c
h
a
o
ti
c
c
a
t
m
a
p
s
,”
Ch
a
o
s,
S
o
li
t
o
n
s
a
n
d
Fr
a
c
ta
ls
,
v
o
l.
2
1
,
n
o
.
3
,
p
p
.
7
4
9
-
7
6
1
,
J
u
ly
2
0
0
4
.
[1
8
]
M
a
o
Y.,
C
h
e
n
Y
.
a
n
d
Li
a
n
S
.
A
.,
“
No
v
e
l
fa
st
ima
g
e
e
n
c
r
y
p
ti
o
n
sc
h
e
m
e
b
a
se
d
o
n
3
D
c
h
a
o
ti
c
b
a
k
e
r
m
a
p
s
,
In
t
e
rn
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Bi
f
u
rc
a
ti
o
n
a
n
d
C
h
a
o
s
,
v
o
l.
1
4
,
n
o
.
1
0
,
No
v
e
m
b
e
r
2
0
1
1
.
[1
9
]
S
e
n
c
a
r
H.
T.
,
Ra
m
k
u
m
a
r
M
.
,
A
k
a
n
su
A.
N
.
,
“
Da
ta
h
id
i
n
g
fu
n
d
a
m
e
n
tals
a
n
d
a
p
p
li
c
a
ti
o
n
s
.
”
Ne
w
Y
o
rk
,
E
lse
v
ier
Aca
d
e
mic
Pre
ss
,
2
0
0
4
.
[2
0
]
Ch
a
n
g
C.
C
.
,
Li
n
C.
C.
,
Ch
e
n
Y.
H.
,
“
Re
v
e
rsib
le
d
a
ta
-
e
m
b
e
d
d
i
n
g
sc
h
e
m
e
u
sin
g
d
i
ffe
re
n
c
e
s
b
e
twe
e
n
o
rig
in
a
l
a
n
d
p
re
d
icte
d
p
ix
e
l
v
a
lu
e
s
.
”
IE
T
In
f
o
r
ma
ti
o
n
S
e
c
u
rity
,
v
o
l.
2
,
n
o
.
2
,
p
p
.
3
5
-
4
6
,
Ju
n
e
2
0
0
8
.
[
2
1
]
H
u
s
s
e
i
n
M
.
K
.
,
A
b
d
u
l
-
K
a
r
e
e
m
H
.
,
“
V
i
d
e
o
c
o
m
p
r
e
s
s
i
o
n
f
o
r
c
o
m
m
u
n
i
c
a
t
i
o
n
a
n
d
s
t
o
r
a
g
e
u
s
i
n
g
w
a
v
e
l
e
t
t
r
a
n
s
f
o
r
m
a
n
d
a
d
a
p
t
i
v
e
r
o
o
d
p
a
t
t
e
r
n
s
e
a
r
c
h
m
a
t
c
h
i
n
g
a
l
g
o
r
i
t
h
m
,”
Al
-
M
u
s
t
a
n
s
i
r
i
y
a
h
J
o
u
r
n
a
l
o
f
S
c
i
e
n
c
e
,
v
o
l
.
2
4
,
n
o
.
5
,
p
p
.
3
9
3
-
4
0
6
,
2
0
1
3
.
[2
2
]
Dira
n
k
o
v
D.,
He
ll
e
n
d
r
o
n
H.
a
n
d
Re
in
fra
n
k
M
.
,
“
An
in
t
ro
d
u
c
ti
o
n
t
o
fu
z
z
y
c
o
n
tr
o
l
,”
S
p
ri
n
g
e
r Ne
w
Y
o
rk
.
1
9
9
3
.
[2
3
]
Ha
id
e
r
M
.
,
Al
-
M
a
sh
h
a
d
i,
Im
a
n
Q
.
Ab
d
u
lj
a
lee
l,
“
Co
l
o
r
ima
g
e
e
n
c
ry
p
ti
o
n
u
si
n
g
c
h
a
o
ti
c
m
a
p
s,
tr
ian
g
u
l
a
r
sc
ra
m
b
li
n
g
,
with
DNA
se
q
u
e
n
c
e
s
,
”
In
ter
n
a
t
io
n
a
l
C
o
n
fer
e
n
c
e
o
n
Cu
rr
e
n
t
R
e
se
a
rc
h
in
Co
m
p
u
ter
S
c
ien
c
e
a
n
d
I
n
fo
rm
a
ti
o
n
T
e
c
h
n
o
l
o
g
y
(ICCI
T
)
,
p
p
.
9
3
-
98
,
Ap
ril
2
0
1
7
.
[2
4
]
Ha
id
e
r
M
.
,
Al
-
M
a
sh
a
d
i,
Ala
'
a
A.
Kh
a
laf,
“
Hy
b
rid
h
o
m
o
m
o
rp
h
ic
c
r
y
p
t
o
sy
ste
m
fo
r
se
c
u
re
tran
sfe
r
o
f
c
o
lo
r
ima
g
e
o
n
p
u
b
li
c
c
lo
u
d
,
”
J
o
u
rn
a
l
o
f
T
h
e
o
re
t
ica
l
a
n
d
Ap
p
li
e
d
I
n
f
o
rm
a
ti
o
n
T
e
c
h
n
o
lo
g
y
,
v
o
l
.
9
6
,
n
o
.
1
9
,
p
p
.
6
4
7
4
-
6
4
8
6
,
2
0
1
8
.
[2
5
]
M
it
a
im,
S
a
n
y
a
,
a
n
d
Ba
rt
Ko
s
k
o
,
“
Th
e
sh
a
p
e
o
f
f
u
z
z
y
se
ts
i
n
a
d
a
p
t
iv
e
fu
n
c
ti
o
n
a
p
p
r
o
x
ima
ti
o
n
.
”
I
EE
E
T
ra
n
sa
c
ti
o
n
s
on
F
u
zz
y
S
y
ste
ms
,
v
o
l.
9
,
n
o
.
4
,
p
p
.
6
3
7
-
6
5
6
,
A
u
g
u
st
2
0
0
1
.
[2
6
]
S
c
h
m
id
t
M
.
,
S
ti
d
se
n
T.
,
“
Hy
p
ri
d
sy
ste
m
:
g
e
n
e
ti
c
a
lg
o
rit
h
m
s,
n
e
u
ra
l
n
e
two
r
k
s,
a
n
d
fu
z
z
y
lo
g
ic
.
”
De
n
ma
rk
.
1
9
9
6
.
[2
7
]
Hu
ss
e
in
M
.
K.
,
“
En
c
ry
p
ti
o
n
o
f
ste
re
o
ima
g
e
s
a
fter
e
stim
a
ted
th
e
m
o
ti
o
n
u
sin
g
sp
a
ti
a
ll
y
d
e
p
e
n
d
e
n
t
a
lg
o
r
it
h
m
s
.
”
In
ter
n
a
t
io
n
a
l
J
o
u
rn
a
l
o
f
C
o
mp
u
ter
S
c
ien
c
e
a
n
d
M
o
b
il
e
Co
m
p
u
ti
n
g
,
v
o
l
.
5
,
n
o
.
1
2
,
p
p
.
1
5
0
-
1
5
9
,
De
c
e
m
b
e
r
2
0
1
6
.
B
I
O
G
RAP
H
I
E
S
O
F
AUTH
O
RS
Ma
r
wa
h
K
.
H
u
ss
e
in
is
a
lec
tu
re
r
in
c
o
m
p
u
ter
in
f
o
rm
a
ti
o
n
s
y
ste
m
s
sin
c
e
(2
0
1
3
),
U
n
iv
e
rsit
y
o
f
Ba
sra
i
n
Ira
q
.
He
r
c
u
rre
n
t
re
s
e
a
rc
h
in
tere
sts
in
c
l
u
d
e
d
i
n
fo
rm
a
t
io
n
se
c
u
rit
y
,
Vi
d
e
o
a
n
d
ima
g
e
p
ro
c
e
ss
in
g
.
Dr
.
K
a
r
e
e
m
Ra
d
h
i
H
a
ss
a
n
,
is
a
n
a
ss
istan
t
p
ro
fe
ss
o
r
i
n
C
o
m
p
u
ter
s
y
ste
m
d
e
p
a
rtme
n
t,
si
n
c
e
(1
9
9
6
),
u
n
iv
e
rsit
y
o
f
Ba
sra
h
,
Ir
a
q
.
His
c
u
rre
n
t
re
se
a
rc
h
in
tere
s
ts
in
c
lu
d
e
i
n
fo
rm
a
ti
o
n
se
c
u
rit
y
,
I
o
T,
G
IS
,
AI.
Dr
.
H
a
id
e
r
M.
Al
-
Ma
sh
h
a
d
i
,
is
a
p
ro
fe
ss
o
r
i
n
c
o
m
p
u
ter
in
f
o
rm
a
ti
o
n
s
y
ste
m
s
d
e
p
a
rtme
n
t
sin
c
e
2
0
0
3
,
u
n
iv
e
rsit
y
o
f
Ba
sra
h
,
Ira
q
.
His
re
se
a
rc
h
in
tere
sts
in
t
h
e
n
e
two
rk
a
n
d
in
f
o
rm
a
ti
o
n
se
c
u
rit
y
,
I
o
T,
e
m
b
e
d
d
e
d
s
y
ste
m
s,
AI an
d
ima
g
e
p
ro
c
e
ss
in
g
.
Evaluation Warning : The document was created with Spire.PDF for Python.