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o
m
th
e
m
o
ti
v
atio
n
th
a
t
h
u
m
a
n
p
er
ce
p
tio
n
u
n
d
er
s
ta
n
d
s
an
i
m
a
g
e
m
ai
n
l
y
ac
co
r
d
in
g
to
its
lo
w
-
lev
el
f
ea
t
u
r
es,
s
p
ec
if
icall
y
t
h
e
ed
g
e
s
,
w
h
ic
h
ar
e
a
m
ea
s
u
r
e
o
f
t
h
e
s
i
g
n
i
f
ican
ce
o
f
a
lo
ca
l
s
tr
u
ct
u
r
e.
Dete
ctin
g
ac
c
u
r
ate
i
n
f
o
r
m
atio
n
o
f
d
is
to
r
tio
n
lev
e
l
o
n
r
ec
eiv
ed
v
id
eo
s
i
s
an
i
m
p
o
r
tan
t
tech
n
iq
u
e
to
m
ea
s
u
r
e
th
e
v
is
u
al
q
u
alit
y
o
f
tr
an
s
m
itted
v
id
eo
o
v
er
u
n
r
eliab
le
w
ir
ele
s
s
c
h
an
n
el
s
.
Du
r
in
g
p
r
e
-
o
r
p
o
s
t
-
p
r
o
ce
s
s
in
g
,
co
m
p
r
e
s
s
io
n
,
ac
q
u
is
it
io
n
,
tr
an
s
m
is
s
io
n
a
n
d
s
to
r
ag
e,
v
id
eo
f
r
a
m
es
m
a
y
c
h
a
n
g
e
d
u
e
to
v
ar
io
u
s
ar
ti
f
ac
t
s
o
r
n
o
is
e
w
h
ich
i
s
v
ie
w
ed
as d
is
to
r
tio
n
t
h
at
d
eg
r
ad
es
th
e
v
is
u
al
q
u
al
it
y
[
2
]
.
T
h
e
ar
tif
ac
ts
ca
n
b
e
d
iv
id
ed
i
n
to
t
w
o
t
y
p
e
s
,
co
m
p
r
ess
io
n
ar
ti
f
ac
ts
a
n
d
also
tr
an
s
m
is
s
io
n
er
r
o
r
s
.
I
n
th
is
p
ap
er
,
b
o
th
ty
p
es
o
f
er
r
o
r
s
ar
e
in
tr
o
d
u
ce
d
to
th
e
test
ed
s
eq
u
e
n
ce
s
as
it
is
i
m
p
o
r
ta
n
t
to
h
av
e
a
d
iv
er
s
it
y
o
f
d
is
to
r
ted
test
s
eq
u
en
ce
s
.
I
n
th
i
s
w
o
r
k
,
th
e
la
s
t
f
r
a
m
e
i
n
ea
ch
Gr
o
u
p
-
of
-
P
ictu
r
es
(
GOP
)
o
f
th
e
r
ef
er
en
ce
a
n
d
d
is
to
r
ted
f
r
a
m
e
s
ar
e
u
s
ed
as
i
n
p
u
t
s
.
T
h
e
s
y
s
t
e
m
p
r
o
d
u
ce
s
a
n
o
u
tp
u
t
i
n
a
f
o
r
m
o
f
a
v
al
u
e
t
h
at
q
u
an
ti
f
ie
s
th
e
q
u
a
lit
y
o
f
t
h
e
d
is
to
r
ted
v
is
u
al
s
i
g
n
a
l.
I
n
v
i
d
eo
tr
an
s
m
is
s
io
n
w
ir
ele
s
s
n
et
w
o
r
k
s
,
th
er
e
is
r
ath
er
li
m
ited
s
u
p
p
o
r
t
f
o
r
b
an
d
w
id
t
h
s
ca
p
ac
ity
.
E
v
en
m
o
r
e,
w
h
e
n
a
r
ed
u
ce
d
-
r
ef
er
en
ce
m
e
tr
ic
is
i
m
p
le
m
en
t
ed
o
n
th
e
v
id
eo
tr
an
s
m
is
s
io
n
,
a
s
id
e
in
f
o
r
m
atio
n
w
o
u
ld
n
ee
d
to
b
e
tr
an
s
m
itte
d
v
ia
an
cillar
y
ch
a
n
n
el
w
it
h
s
o
m
e
in
f
o
r
m
a
tio
n
f
r
o
m
t
h
e
r
ef
er
en
ce
v
id
eo
.
T
h
er
ef
o
r
e,
it
is
p
er
tin
e
n
t
to
h
av
e
lo
w
o
v
er
h
ea
d
b
itra
te
f
o
r
th
e
s
id
e
i
n
f
o
r
m
atio
n
s
id
e.
I
n
[
3
]
,
a
n
o
v
el
E
DI
R
R
m
etr
ic
h
as
b
ee
n
p
r
o
p
o
s
ed
,
w
h
er
e
its
ass
e
s
s
m
e
n
t
h
as
b
ee
n
f
o
u
n
d
to
co
r
r
elate
w
ell
w
i
th
D
MO
S
o
b
tain
ed
f
r
o
m
L
I
V
E
.
Ho
w
ev
er
,
s
i
n
ce
th
e
o
v
er
h
ea
d
b
itra
tes
f
r
o
m
t
h
e
m
etr
ic
ar
e
n
o
t
s
u
f
f
ic
ien
t
l
y
l
o
w
(
2
.
8
Mb
p
s
)
,
an
in
v
e
s
ti
g
atio
n
f
o
cu
s
e
s
o
n
co
m
p
r
ess
in
g
a
n
d
e
v
alu
a
tin
g
th
e
ab
ilit
y
o
f
t
h
e
m
etr
ic
af
ter
b
ein
g
co
m
p
r
es
s
ed
is
p
r
o
p
o
s
ed
to
b
e
in
v
e
s
ti
g
ated
in
t
h
is
p
ap
er
.
T
h
e
co
m
p
r
ess
i
o
n
p
er
f
o
r
m
a
n
ce
i
s
i
n
v
e
s
ti
g
a
ted
b
y
lo
o
k
i
n
g
a
t
d
if
f
er
e
n
t
co
m
b
i
n
atio
n
s
o
f
s
p
at
ial
an
d
te
m
p
o
r
al
r
eso
lu
tio
n
s
.
T
h
is
alg
o
r
ith
m
allo
w
s
a
n
e
f
f
e
ctiv
e
as
s
es
s
m
e
n
t
o
f
r
ed
u
ce
d
-
r
ef
er
en
ce
v
id
eo
q
u
alit
y
w
it
h
m
u
c
h
lo
w
er
o
v
er
h
ea
d
co
s
t.
2.
RE
S
E
ARCH
M
E
T
H
O
D
T
h
e
p
r
o
p
o
s
ed
R
R
m
etr
ic
i
n
th
is
p
ap
er
is
p
er
f
o
r
m
ed
b
y
c
o
m
p
ar
i
n
g
t
h
e
ed
g
e
i
n
f
o
r
m
ati
o
n
o
f
th
e
o
r
ig
in
al
an
d
d
is
to
r
ted
s
eq
u
e
n
c
e
in
ter
m
s
o
f
s
tr
u
ct
u
r
al
d
is
to
r
t
io
n
.
T
h
e
ed
g
e
d
e
g
r
ad
atio
n
ca
n
b
e
d
etec
ted
in
th
i
s
m
an
n
er
a
s
i
t
i
s
h
i
g
h
l
y
a
s
s
o
ci
ated
w
ith
t
h
e
s
tr
u
ct
u
r
al
ed
g
e.
T
h
e
d
ev
elo
p
m
e
n
t
o
f
t
h
e
ed
g
e
-
b
a
s
ed
d
is
to
r
tio
n
m
ea
s
u
r
e
is
b
y
as
s
es
s
in
g
t
h
e
d
ec
o
d
ed
g
r
ey
s
ca
le
i
m
a
g
es.
T
h
e
lo
w
-
le
v
el
co
n
te
n
t
o
f
v
is
u
al
i
m
p
o
r
tan
ce
o
r
s
alien
t
i
m
a
g
e
f
ea
tu
r
es
s
u
ch
a
s
t
h
e
ed
g
e
i
n
ten
s
it
y
d
ef
i
n
itel
y
h
as
i
m
a
g
e
i
n
f
o
r
m
atio
n
a
n
d
th
is
i
s
p
er
ce
p
tu
all
y
i
m
p
o
r
tan
t.
T
h
er
ef
o
r
e,
u
s
i
n
g
t
h
is
o
b
s
er
v
at
io
n
,
t
h
e
ed
g
e
i
n
f
o
r
m
atio
n
is
i
n
co
r
p
o
r
ated
in
to
th
e
R
R
d
is
s
i
m
ilar
it
y
m
ea
s
u
r
e
to
d
ev
elo
p
v
id
eo
q
u
alit
y
i
n
d
ices
–
E
DI
R
R
: E
d
g
e
-
b
ased
Dis
s
i
m
ilar
it
y
R
ed
u
ce
d
R
e
f
er
en
ce
Me
tr
ic.
T
h
e
test
s
eq
u
en
ce
s
ar
e
o
b
tain
ed
f
r
o
m
t
h
e
L
ab
o
r
ato
r
y
f
o
r
I
m
ag
e
&
Vid
eo
(
L
I
VE
)
Vid
eo
Data
b
ase
[
2
6
]
an
d
th
e
p
r
o
p
o
s
ed
m
etr
ic
w
o
u
ld
b
e
test
ed
ag
ai
n
s
t
th
e
s
u
b
j
ec
tiv
e
q
u
alit
y
s
co
r
e,
Dif
f
er
e
n
tial
Me
a
n
Op
i
n
io
n
Sco
r
e
(
DM
OS)
,
p
r
o
v
id
ed
f
r
o
m
t
h
e
s
u
b
j
ec
tiv
e
s
t
u
d
y
ca
r
r
ie
d
o
u
t
b
y
L
I
VE
[
2
7
,
2
8
]
.
T
h
e
DM
OS
v
alu
e
s
r
an
g
e
f
r
o
m
0
to
1
0
0
,
w
h
er
e
th
e
s
m
aller
v
alu
e
ex
p
r
es
s
es
th
e
g
r
ea
ter
q
u
alit
y
an
d
th
e
lar
g
er
v
al
u
e
s
tates
t
h
e
w
o
r
s
e
q
u
alit
y
,
ar
e
co
llected
u
s
i
n
g
th
e
s
u
b
j
ec
tiv
e
test
m
o
d
el
s
p
ec
i
f
ied
in
I
T
U
-
R
B
T
5
0
0
.
1
1
[
2
9
-
3
1
]
.
T
h
e
s
u
b
j
ec
tiv
e
s
tu
d
y
w
as
co
n
d
u
c
ted
u
s
i
n
g
a
s
in
g
le
s
ti
m
u
l
u
s
p
r
o
ce
d
u
r
e
w
i
t
h
h
id
d
en
r
ef
er
en
ce
r
e
m
o
v
al
an
d
th
e
s
u
b
j
ec
ts
in
d
icate
d
t
h
e
q
u
al
it
y
o
f
th
e
v
i
d
eo
o
n
a
co
n
ti
n
u
o
u
s
s
ca
le.
Su
b
j
ec
ts
also
v
ie
w
ed
ea
c
h
o
f
t
h
e
r
ef
er
en
ce
v
id
eo
s
to
f
ac
ilit
ate
co
m
p
u
tat
io
n
o
f
d
i
f
f
e
r
en
ce
s
co
r
es
u
s
in
g
h
id
d
en
r
ef
er
en
ce
r
e
m
o
v
al.
Fro
m
th
e
d
at
ab
ase,
8
0
d
i
s
to
r
ted
v
id
eo
s
eq
u
e
n
ce
s
w
er
e
o
b
tain
ed
f
r
o
m
1
0
d
if
f
er
e
n
t
h
ig
h
-
q
u
alit
y
v
id
eo
s
w
it
h
a
w
id
e
v
ar
iet
y
o
f
co
n
te
n
t
a
s
r
ef
er
en
ce
v
id
eo
s
.
A
s
et
o
f
8
0
d
is
to
r
ted
v
id
eo
s
a
r
e
test
ed
u
s
in
g
t
w
o
d
i
f
f
er
en
t
d
is
to
r
tio
n
t
y
p
e
s
:
H.
2
6
4
co
m
p
r
ess
io
n
an
d
s
i
m
u
lated
tr
an
s
m
is
s
io
n
o
f
H.
2
6
4
co
m
p
r
ess
ed
b
its
tr
ea
m
s
t
h
r
o
u
g
h
er
r
o
r
-
p
r
o
n
e
w
ir
eless
n
et
w
o
r
k
s
,
as
th
ese
t
y
p
e
o
f
d
is
to
r
tio
n
s
r
elate
t
h
e
m
o
s
t
t
o
th
e
w
o
r
k
p
er
f
o
r
m
ed
in
th
is
c
h
ap
ter
.
T
h
e
d
iv
er
s
it
y
o
f
d
is
to
r
tio
n
t
y
p
es
i
s
to
test
th
e
ab
ilit
y
o
f
t
h
e
p
r
o
p
o
s
ed
o
b
jectiv
e
m
o
d
el
to
p
r
ed
ict
v
i
s
u
a
l
q
u
alit
y
co
n
s
i
s
te
n
tl
y
ac
r
o
s
s
d
is
t
o
r
tio
n
s
.
T
h
e
H.
2
6
4
co
m
p
r
es
s
io
n
s
y
s
te
m
p
r
o
d
u
ce
s
f
air
l
y
u
n
i
f
o
r
m
s
p
atial
a
n
d
te
m
p
o
r
al
d
is
to
r
tio
n
s
i
n
th
e
v
id
e
o
.
Net
w
o
r
k
lo
s
s
es,
h
o
w
ev
er
,
ca
u
s
e
tr
a
n
s
ie
n
t
d
is
t
o
r
tio
n
s
in
th
e
v
id
eo
,
b
o
th
s
p
atiall
y
a
n
d
te
m
p
o
r
all
y
.
T
h
e
H.
2
6
4
co
m
p
r
ess
ed
v
id
eo
s
ex
h
ib
it
a
v
is
u
al
ap
p
ea
r
an
ce
o
f
t
y
p
ical
co
m
p
r
ess
io
n
ar
tif
ac
t
s
s
u
ch
a
s
b
lu
r
,
b
lo
ck
i
n
g
,
r
in
g
i
n
g
an
d
m
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E
r
r
o
r
s
s
u
s
t
ain
ed
b
y
a
n
H.
2
6
4
co
m
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ed
v
id
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tr
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y
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lized
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ter
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ce
in
w
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
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w
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las
t
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f
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ted
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Data
b
ase
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as
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etr
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3.
RE
SU
L
T
S
A
ND
M
E
T
H
O
D
T
h
e
p
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p
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R
R
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m
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ated
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d
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it
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q
u
alit
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n
d
ices
–
E
DI
R
R
: E
d
g
e
-
b
ased
Dis
s
i
m
ilar
it
y
R
ed
u
ce
d
R
e
f
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ce
Me
tr
ic.
T
h
e
test
s
eq
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en
ce
s
ar
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o
b
tain
ed
f
r
o
m
t
h
e
L
ab
o
r
ato
r
y
f
o
r
I
m
ag
e
&
Vid
eo
(
L
I
VE
)
Vid
eo
Data
b
ase
[
2
6
]
an
d
th
e
p
r
o
p
o
s
ed
m
etr
ic
w
o
u
ld
b
e
test
ed
ag
ai
n
s
t
th
e
s
u
b
j
ec
tiv
e
q
u
alit
y
s
co
r
e,
Dif
f
er
e
n
tial
Me
a
n
Op
i
n
io
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Sc
o
r
e
(
DM
OS)
,
p
r
o
v
id
ed
f
r
o
m
t
h
e
s
u
b
j
ec
tiv
e
s
t
u
d
y
ca
r
r
ie
d
o
u
t
b
y
L
I
VE
[
2
7
,
2
8
]
.
T
h
e
DM
OS
v
alu
e
s
r
an
g
e
f
r
o
m
0
to
1
0
0
,
w
h
er
e
th
e
s
m
aller
v
alu
e
ex
p
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es
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r
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ter
q
u
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llected
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th
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s
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b
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test
m
o
d
el
s
p
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i
f
ied
in
I
T
U
-
R
B
T
5
0
0
.
1
1
[
2
9
-
3
1
]
.
T
h
e
s
u
b
j
ec
tiv
e
s
tu
d
y
w
as
co
n
d
u
c
ted
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s
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n
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a
s
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ti
m
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l
u
s
p
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ce
d
u
r
e
w
it
h
h
id
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en
r
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ce
r
e
m
o
v
al
an
d
th
e
s
u
b
j
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ts
in
d
icate
d
t
h
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q
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al
it
y
o
f
th
e
v
i
d
eo
o
n
a
co
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ti
n
u
o
u
s
s
ca
le.
Su
b
j
ec
ts
also
v
ie
w
ed
ea
c
h
o
f
t
h
e
r
ef
er
e
n
ce
v
id
eo
s
to
f
ac
ilit
ate
co
m
p
u
tat
io
n
o
f
d
i
f
f
e
r
en
ce
s
co
r
es
u
s
in
g
h
id
d
en
r
ef
er
en
ce
r
e
m
o
v
al.
Fro
m
th
e
d
at
ab
ase,
8
0
d
is
to
r
ted
v
id
eo
s
eq
u
e
n
ce
s
w
er
e
o
b
tain
ed
f
r
o
m
1
0
d
if
f
er
e
n
t
h
ig
h
-
q
u
alit
y
v
id
eo
s
w
it
h
a
w
id
e
v
ar
iet
y
o
f
co
n
te
n
t
a
s
r
ef
er
en
ce
v
id
eo
s
.
A
s
et
o
f
8
0
d
is
to
r
ted
v
id
eo
s
a
r
e
test
ed
u
s
in
g
t
w
o
d
i
f
f
er
en
t
d
is
to
r
tio
n
t
y
p
e
s
:
H.
2
6
4
co
m
p
r
ess
io
n
an
d
s
i
m
u
lated
tr
an
s
m
is
s
io
n
o
f
H.
2
6
4
co
m
p
r
ess
ed
b
its
tr
ea
m
s
t
h
r
o
u
g
h
er
r
o
r
-
p
r
o
n
e
w
ir
eless
n
et
w
o
r
k
s
,
as
th
ese
t
y
p
e
o
f
d
is
to
r
tio
n
s
r
elate
t
h
e
m
o
s
t
t
o
th
e
w
o
r
k
p
er
f
o
r
m
ed
in
th
is
c
h
ap
ter
.
T
h
e
d
iv
er
s
it
y
o
f
d
is
to
r
tio
n
t
y
p
es
i
s
to
test
th
e
ab
ilit
y
o
f
t
h
e
p
r
o
p
o
s
ed
o
b
jectiv
e
m
o
d
el
to
p
r
ed
ict
v
i
s
u
a
l
q
u
alit
y
co
n
s
i
s
te
n
tl
y
ac
r
o
s
s
d
is
t
o
r
tio
n
s
.
T
h
e
H.
2
6
4
co
m
p
r
es
s
io
n
s
y
s
te
m
p
r
o
d
u
ce
s
f
air
l
y
u
n
i
f
o
r
m
s
p
atial
a
n
d
te
m
p
o
r
al
d
is
to
r
tio
n
s
i
n
th
e
v
id
e
o
.
Net
w
o
r
k
lo
s
s
es,
h
o
w
ev
er
,
ca
u
s
e
tr
a
n
s
ie
n
t
d
is
t
o
r
tio
n
s
in
th
e
v
id
eo
,
b
o
th
s
p
atiall
y
a
n
d
te
m
p
o
r
all
y
.
T
h
e
H.
2
6
4
co
m
p
r
ess
ed
v
id
eo
s
ex
h
ib
it
a
v
is
u
al
ap
p
ea
r
an
ce
o
f
t
y
p
ical
co
m
p
r
ess
io
n
ar
tif
ac
t
s
s
u
ch
a
s
b
lu
r
,
b
lo
ck
i
n
g
,
r
in
g
i
n
g
an
d
m
o
tio
n
co
m
p
e
n
s
at
io
n
m
is
m
atc
h
es a
r
o
u
n
d
t
h
e
ed
g
e
s
o
f
t
h
e
m
ai
n
b
o
d
y
i
n
th
e
f
r
a
m
e.
Vid
eo
s
o
b
tain
e
d
f
r
o
m
t
h
e
w
ir
eles
s
tr
an
s
m
is
s
io
n
er
r
o
r
ex
h
ib
it
er
r
o
r
s
th
at
ar
e
r
estricte
d
to
s
m
all
r
eg
io
n
s
o
f
a
f
r
a
m
e.
E
r
r
o
r
s
s
u
s
t
ain
ed
b
y
a
n
H.
2
6
4
co
m
p
r
es
s
ed
v
id
eo
s
tr
ea
m
i
n
a
w
ir
eles
s
e
n
v
ir
o
n
m
e
n
t
ar
e
als
o
s
p
ati
o
-
te
m
p
o
r
all
y
lo
ca
lized
d
is
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8
‘
So
er
g
el
’
i
n
T
ab
le
1
3
r
ep
r
esen
ts
So
er
g
el
d
is
ta
n
ce
m
ea
s
u
r
e,
s
1
r
ep
r
esen
ts
o
r
ig
in
al
s
p
atial
r
eso
lu
tio
n
u
s
i
n
g
So
b
el
ed
g
e
d
etec
to
r
(
f
r
o
m
C
h
ap
ter
4
)
,
c2
r
e
p
r
esen
ts
u
s
in
g
C
a
n
n
y
ed
g
e
d
etec
to
r
an
d
s
u
b
-
s
a
m
p
led
b
y
f
ac
to
r
o
f
2
,
s
2
r
ep
r
esen
ts
u
s
in
g
So
b
el
ed
g
e
d
etec
to
r
an
d
s
u
b
-
s
a
m
p
led
b
y
f
ac
to
r
o
f
2
,
c3
r
ep
r
esen
t
s
u
s
in
g
C
an
n
y
ed
g
e
d
etec
to
r
an
d
s
u
b
-
s
a
m
p
led
b
y
f
ac
to
r
o
f
3
an
d
s
3
r
ep
r
esen
ts
u
s
i
n
g
So
b
el
ed
g
e
d
etec
to
r
an
d
s
u
b
-
s
a
m
p
led
b
y
f
ac
to
r
o
f
3
.
A
ll se
q
u
en
ce
s
h
a
v
e
b
ee
n
d
o
w
n
-
s
a
m
p
led
u
s
in
g
n
ea
r
e
s
t n
ei
g
h
b
o
u
r
in
ter
p
o
latio
n
,
r
e
m
o
v
e
m
o
r
p
h
o
lo
g
ical
f
u
n
ctio
n
an
d
te
m
p
o
r
all
y
r
ed
u
ce
d
to
1
f
p
s
.
5.
CO
NCLU
SI
O
N
T
h
e
m
a
in
ai
m
i
n
t
h
is
p
ap
er
is
to
r
ed
u
ce
s
i
g
n
if
ica
n
tl
y
t
h
e
o
v
er
h
ea
d
b
itra
te
r
eq
u
ir
ed
in
o
r
d
er
t
o
tr
an
s
m
it
th
e
s
id
e
i
n
f
o
r
m
atio
n
w
ith
o
u
t
i
n
f
l
u
en
ci
n
g
t
h
e
r
ed
u
ce
d
r
ef
er
en
ce
v
id
eo
q
u
alit
y
m
etr
ic
p
er
f
o
r
m
an
c
e
f
r
o
m
[
3
]
.
T
h
is
co
n
s
eq
u
e
n
tl
y
ev
o
lv
e
s
to
b
ec
o
m
e
a
m
o
d
if
i
e
d
E
DI
R
R
,
a
r
ed
u
ce
d
r
ef
er
e
n
ce
b
ased
o
n
ed
g
e
d
is
s
i
m
ilar
it
y
w
i
th
lo
w
o
v
er
h
e
ad
b
itra
te.
Vid
eo
q
u
alit
y
m
etr
ics
ar
e
es
s
e
n
tial
i
n
r
e
f
lecti
n
g
t
h
e
p
er
ce
iv
ed
v
id
eo
q
u
alit
y
ac
c
u
r
atel
y
an
d
t
h
e
y
s
h
o
u
ld
co
r
r
elate
w
e
ll
w
it
h
s
u
b
j
ec
tiv
e
q
u
alit
y
ass
e
s
s
m
e
n
t
o
f
th
e
tes
t
s
eq
u
e
n
ce
s
.
T
h
e
co
r
r
elatio
n
co
ef
f
icie
n
t
s
b
et
w
ee
n
t
h
e
r
es
u
lt
in
g
So
er
g
el
d
is
tan
ce
m
ea
s
u
r
e
s
eq
u
e
n
ce
s
te
m
p
o
r
all
y
r
ed
u
ce
d
to
1
f
p
s
w
it
h
L
I
VE
DM
OS
s
co
r
e
ar
e
p
r
esen
ted
i
n
T
ab
le
7
.
I
t
s
h
o
w
s
t
h
at
t
h
e
s
id
e
in
f
o
r
m
at
io
n
ex
tr
ac
ted
u
s
in
g
So
b
el
ed
g
e
d
etec
to
r
m
ai
n
tai
n
ed
co
n
s
is
t
e
n
c
y
t
h
r
o
u
g
h
o
u
t
t
h
e
r
ed
u
ctio
n
i
n
b
o
th
i
n
s
p
atial
a
n
d
te
m
p
o
r
al
d
o
w
n
-
s
a
m
p
le
co
n
s
id
er
ab
l
y
w
it
h
t
h
e
a
m
o
u
n
t
o
f
in
f
o
r
m
at
io
n
a
v
ail
ab
le.
T
h
e
co
r
r
elatio
n
s
u
s
i
n
g
C
an
n
y
ed
g
e
d
etec
to
r
ar
e
al
m
o
s
t
s
i
m
ilar
to
t
h
e
p
r
ev
io
u
s
So
er
g
el
m
ea
s
u
r
e
w
it
h
o
u
t
an
y
d
o
w
n
-
s
a
m
p
li
n
g
b
u
t
t
h
e
y
ar
e
n
o
t
th
o
r
o
u
g
h
l
y
co
n
s
is
ten
t.
T
h
e
in
co
n
s
i
s
te
n
c
y
o
n
l
y
o
cc
u
r
r
ed
o
n
test
s
eq
u
e
n
c
es
w
ith
f
a
s
t
m
o
tio
n
an
d
a
lo
t
o
f
tex
t
u
r
es.
T
h
is
i
s
in
f
lu
e
n
ce
d
b
y
th
e
C
a
n
n
y
ed
g
e
d
etec
to
r
w
h
ich
d
etec
ts
m
o
r
e
d
etails
t
h
an
So
b
el
ed
g
e
d
etec
t
o
r
an
d
in
cr
ea
s
e
s
t
h
e
p
r
o
b
a
b
ilit
y
to
ca
p
tu
r
e
th
e
w
ea
k
ed
g
es.
T
h
e
p
r
o
b
lem
m
a
y
b
e
s
o
lv
ed
b
y
in
cr
ea
s
in
g
t
h
e
th
r
e
s
h
o
ld
b
u
t
a
h
ig
h
er
th
r
es
h
o
ld
ca
u
s
es
th
e
i
n
ab
ilit
y
to
ca
p
tu
r
e
t
h
e
m
ai
n
s
tr
u
c
tu
r
e
af
ter
d
o
w
n
-
s
a
m
p
li
n
g
a
n
d
r
e
m
o
v
e
m
o
r
p
h
o
lo
g
ica
l
f
u
n
ctio
n
ap
p
lied
ac
co
r
d
in
g
to
p
r
io
r
in
itial
test
.
R
es
u
lt
s
als
o
s
h
o
w
t
h
e
p
o
s
s
ib
ilit
y
to
tr
an
s
m
it
t
h
e
s
id
e
in
f
o
r
m
atio
n
w
h
et
h
er
it
is
d
o
w
n
-
s
a
m
p
led
to
f
ac
to
r
o
f
th
r
ee
a
n
d
ev
e
n
f
ac
to
r
o
f
t
w
o
i
f
t
h
e
p
o
ten
tial
b
a
n
d
w
id
th
allo
w
a
n
ce
is
co
n
v
e
n
ie
n
t a
s
t
h
e
b
itra
te
o
f
th
e
o
v
er
h
ea
d
is
v
er
y
s
m
all.
ACK
NO
WL
E
D
G
E
M
E
NT
S
T
h
e
au
th
o
r
s
a
c
k
n
o
w
led
g
e
t
h
e
f
i
n
an
cia
l
as
s
is
ta
n
ce
o
f
th
i
s
r
esear
ch
w
h
ich
is
s
u
p
p
o
r
ted
b
y
t
h
e
R
esear
ch
I
n
itiati
v
e
Gr
a
n
t
Sc
h
e
m
e
(
R
I
GS)
w
it
h
t
h
e
g
r
an
t
n
u
m
b
er
R
I
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6
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087
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0
2
5
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d
I
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t
er
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atio
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al
I
s
la
m
ic
Un
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v
er
s
it
y
Ma
la
y
s
ia
(
I
I
UM
)
.
RE
F
E
R
E
NC
E
S
[1
]
M
.
Ča
d
ík
.
Hu
m
a
n
p
e
rc
e
p
ti
o
n
a
n
d
c
o
m
p
u
ter
g
ra
p
h
ics
.
P
o
stg
ra
d
u
a
te
S
tu
d
y
Re
p
o
rt,
Cz
e
c
h
T
e
c
h
n
ica
l
Un
iv
e
rsit
y
.
2
0
0
4
.
[2
]
S
.
W
in
k
ler,
M
.
Ku
n
t,
a
n
d
C
.
J.
v
a
n
d
e
n
Bra
n
d
e
n
L
a
m
b
re
c
h
t.
V
isi
o
n
a
n
d
v
id
e
o
:
m
o
d
e
ls
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n
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p
p
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ica
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o
n
s.
V
isio
n
M
o
d
e
ls a
n
d
A
p
p
li
c
a
ti
o
n
s t
o
Im
a
g
e
a
n
d
Vi
d
e
o
Pro
c
e
ss
in
g
.
S
p
ri
n
g
e
r
.
2
0
0
1
:
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0
1
-
2
2
9
.
[3
]
F
.
D.
A
b
d
u
l
Ra
h
m
a
n
,
e
t
a
l.
.
Red
u
c
e
d
-
Refe
re
n
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Vi
d
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o
Qu
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ty
M
e
tric
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se
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o
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E
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rm
a
ti
o
n
.
P
ro
c
e
e
d
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n
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o
f
4
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IEE
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In
tern
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ti
o
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l
Co
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n
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m
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rt
In
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n
tatio
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s
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0
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[4
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T
.
Oja
la,
M
.
P
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a
in
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n
,
a
n
d
T
.
M
a
e
n
p
a
a
.
M
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ra
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n
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ti
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n
w
it
h
lo
c
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b
in
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s
.
IEE
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Pa
tt
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rn
An
a
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d
M
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2
0
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7
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8
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.
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9
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I
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No
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2
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Feb
r
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0
1
8
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–
640
640
[6
]
M
.
Zh
a
n
g
,
J.
X
ie,
X
.
Zh
o
u
,
a
n
d
H.
F
u
ji
ta.
No
re
f
e
re
n
c
e
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m
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g
e
q
u
a
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ty
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ss
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e
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t
b
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se
d
o
n
lo
c
a
l
b
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n
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ry
p
a
tt
e
rn
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ti
stics
.
Vi
su
a
l
Co
mm
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io
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n
d
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g
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Pro
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e
ss
in
g
(
VCIP
)
.
2
0
1
3
:
1
-
6.
[7
]
X
.
Cu
i
,
Z.
S
h
i
,
J.
L
in
,
a
n
d
L
.
Hu
a
n
g
.
T
h
e
R
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se
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r
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m
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Qu
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ty
As
se
s
s
m
e
n
t
M
e
th
o
d
s.
Ph
y
sic
s
Pro
c
e
d
ia
.
2
0
1
2
;
2
5
(
0
):
4
8
5
-
4
9
1
.
[8
]
S
.
Ra
k
sh
it
,
a
n
d
A
.
M
i
sh
ra
.
Esti
m
a
ti
o
n
o
f
S
tru
c
tu
ra
l
I
n
f
o
rm
a
ti
o
n
C
o
n
ten
t
in
Im
a
g
e
s.
Co
mp
u
ter
Vi
sio
n
(
ACCV
).
2
0
0
6
:
2
6
5
-
2
7
5
.
[9
]
X
.
M
o
u
,
M
.
Zh
a
n
g
,
W
.
X
u
e
,
a
n
d
L
.
Zh
a
n
g
.
Im
a
g
e
q
u
a
li
ty
a
ss
e
s
s
m
e
n
t
b
a
se
d
o
n
e
d
g
e
.
IS
&
T
/S
PIE
El
e
c
tro
n
ic
Ima
g
i
n
g
.
2
0
1
1
:
7
8
7
6
0
N
-
7
8
7
6
0
N
-
9.
[1
0
]
X
.
F
e
i
,
L
.
X
iao
,
Y
.
S
u
n
,
a
n
d
Z.
W
e
i.
P
e
rc
e
p
tu
a
l
im
a
g
e
q
u
a
li
t
y
a
s
se
ss
m
e
n
t
b
a
se
d
o
n
stru
c
tu
ra
l
sim
il
a
rit
y
a
n
d
v
isu
a
l
m
a
sk
in
g
.
S
ig
n
a
l
Pro
c
e
ss
in
g
:
Ima
g
e
Co
mm
u
n
ica
ti
o
n
.
2
0
1
2
;
2
7
(
7
):
7
7
2
-
7
8
3
.
[1
1
]
L
.
Zh
ich
a
o
,
T
.
Jin
x
u
,
a
n
d
Z.
Zh
u
f
e
n
g
.
Red
u
c
e
d
-
re
fer
e
n
c
e
im
a
g
e
q
u
a
li
ty
a
ss
e
ss
me
n
t
b
a
se
d
o
n
a
v
e
ra
g
e
d
ire
c
ti
o
n
a
l
i
n
fo
rm
a
ti
o
n
.
2
0
1
2
IE
EE
1
1
th
In
tern
a
ti
o
n
a
l
Co
n
f
e
re
n
c
e
o
n
S
ig
n
a
l
P
r
o
c
e
ss
in
g
(ICS
P
).
2
0
1
2
:
7
8
7
-
7
9
1
.
[1
2
]
R.
A
n
d
e
rso
n
,
N.
Kin
g
sb
u
ry
,
a
n
d
J.
F
a
u
q
u
e
u
r.
De
term
in
in
g
m
u
l
ti
sc
a
le
i
m
a
g
e
fe
a
tu
re
a
n
g
le
s
f
ro
m
c
o
m
p
lex
w
a
v
e
let
p
h
a
se
s
.
Ima
g
e
An
a
lys
is a
n
d
Rec
o
g
n
i
ti
o
n
.
2
0
0
5
:
4
9
0
-
4
9
8
.
[1
3
]
P
.
M
a
rz
il
ian
o
,
F
.
Du
f
a
u
x
,
S
.
W
in
k
ler,
a
n
d
T
.
Eb
ra
h
im
i.
P
e
rc
e
p
t
u
a
l
b
l
u
r
a
n
d
rin
g
i
n
g
m
e
tri
c
s:
a
p
p
li
c
a
ti
o
n
to
JP
EG
2
0
0
0
.
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
:
I
ma
g
e
Co
mm
u
n
ica
t
io
n
.
2
0
0
4
;
1
9
(
2
):
1
6
3
-
1
7
2
.
[1
4
]
E.
On
g
,
W
.
L
in
,
Z.
L
u
,
X.
Ya
n
g
,
S
.
Ya
o
,
F
.
P
a
n
,
L
.
Jia
n
g
,
a
n
d
F
.
M
o
sc
h
e
tt
i
.
A
n
o
-
re
fer
e
n
c
e
q
u
a
l
it
y
me
tric
fo
r
me
a
su
rin
g
ima
g
e
b
lu
rs
.
7
t
h
I
n
te
rn
a
ti
o
n
a
l
S
y
m
p
o
siu
m
o
n
S
ig
n
a
l
P
r
o
c
e
ss
in
g
a
n
d
Its
A
p
p
li
c
a
ti
o
n
s.
2
0
0
3
:
4
6
9
-
4
7
2
.
[1
5
]
X
.
Ra
n
,
a
n
d
N.
F
a
rv
a
rd
in
.
A
p
e
rc
e
p
tu
a
ll
y
m
o
ti
v
a
ted
th
re
e
-
c
o
m
p
o
n
e
n
t
im
a
g
e
m
o
d
e
l
-
P
a
rt
I:
d
e
sc
rip
ti
o
n
o
f
th
e
m
o
d
e
l.
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Ima
g
e
Pro
c
e
ss
in
g
.
1
9
9
5
;
4
(
4
):
4
0
1
-
4
1
5
.
[1
6
]
M
.
S
.
P
rieto
,
a
n
d
A
.
R.
A
ll
e
n
.
A
sim
il
a
rit
y
m
e
tri
c
f
o
r
e
d
g
e
i
m
a
g
e
s.
IEE
E
T
r
a
n
s
a
c
ti
o
n
s
o
n
P
a
tt
e
rn
A
n
a
lys
is
a
n
d
M
a
c
h
in
e
In
telli
g
e
n
c
e
.
2
0
0
3
;
2
5
(1
0
):
1
2
6
5
-
1
2
7
3
.
[1
7
]
M
.
A
.
Ro
d
ríg
u
e
z
-
Día
z
,
a
n
d
H.
S
á
n
c
h
e
z
-
Cru
z
.
Re
f
in
e
d
f
ix
e
d
d
o
u
b
le
p
a
ss
b
i
n
a
ry
o
b
jec
t
c
las
s
if
ica
ti
o
n
f
o
r
d
o
c
u
m
e
n
t
im
a
g
e
c
o
m
p
re
ss
io
n
.
Di
g
it
a
l
S
i
g
n
a
l
Pr
o
c
e
ss
in
g
.
2
0
1
4
;
3
0
(0
):
1
1
4
-
1
3
0
.
[1
8
]
Y.
Ya
e
g
a
sh
i,
K.
T
a
teo
k
a
,
K.
F
u
ji
m
o
to
,
T
.
N
a
k
a
z
a
w
a
,
A
.
Na
k
a
ta,
Y.
S
a
it
o
,
T
.
A
b
e
,
M
.
Y
a
n
o
,
a
n
d
K.
S
a
k
a
ta.
A
s
se
ss
m
e
n
t
o
f
S
im
il
a
rit
y
M
e
a
su
r
e
s
f
o
r
A
c
c
u
ra
te
De
f
o
r
m
a
b
le
I
m
a
g
e
Re
g
istratio
n
.
J
o
u
rn
a
l
o
f
Nu
c
lea
r
M
e
d
icin
e
&
Ra
d
ia
ti
o
n
T
h
e
ra
p
y
.
2
0
1
2
.
[1
9
]
P
.
W
il
lett,
J.
M
.
Ba
rn
a
r
d
,
a
n
d
G
.
M
.
Do
w
n
s.
Ch
e
m
ica
l
si
m
il
a
rit
y
se
a
rc
h
in
g
.
J
o
u
rn
a
l
o
f
c
h
e
mic
a
l
i
n
fo
rm
a
t
io
n
a
n
d
c
o
mp
u
ter
sc
ien
c
e
s
.
1
9
9
8
;
3
8
(
6
):
9
8
3
-
9
9
6
.
[2
0
]
M
.
Ko
w
a
lcz
y
k
,
P
.
Ko
z
a
,
P
.
K
u
p
id
u
ra
,
a
n
d
J.
M
a
rc
in
iak
.
A
p
p
li
c
a
t
io
n
o
f
m
a
th
e
m
a
ti
c
a
l
m
o
rp
h
o
lo
g
y
o
p
e
ra
ti
o
n
s
f
o
r
si
m
p
li
f
ica
ti
o
n
a
n
d
im
p
ro
v
e
m
e
n
t
o
f
c
o
rre
latio
n
o
f
i
m
a
g
e
s
in
c
lo
se
-
ra
n
g
e
p
h
o
to
g
ra
m
m
e
tr
y
.
T
h
e
in
ter
n
a
ti
o
n
a
l
a
rc
h
ive
s o
f
t
h
e
p
h
o
t
o
g
r
a
mm
e
try
,
re
mo
te se
n
sin
g
a
n
d
sp
a
ti
a
l
i
n
fo
r
ma
ti
o
n
sc
ien
c
e
s
.
2
0
0
8
;
3
7
:
1
5
3
-
8.
[2
1
]
R.
Krish
n
a
p
u
ra
m
,
a
n
d
S
.
G
u
p
ta.
M
o
rp
h
o
l
o
g
ica
l
m
e
th
o
d
s
f
o
r
d
e
t
e
c
ti
o
n
a
n
d
c
las
sif
ic
a
ti
o
n
o
f
e
d
g
e
s
in
ra
n
g
e
im
a
g
e
s.
J
o
u
rn
a
l
o
f
M
a
t
h
e
ma
ti
c
a
l
Ima
g
i
n
g
a
n
d
Vi
si
o
n
.
1
9
9
2
;
2
(4
):
3
5
1
-
3
7
5
.
[2
2
]
R.
M
.
Ha
ra
li
c
k
,
S
.
R.
S
tern
b
e
rg
,
a
n
d
X
.
Zh
u
a
n
g
.
Im
a
g
e
a
n
a
l
y
sis
u
sin
g
m
a
th
e
m
a
ti
c
a
l
m
o
rp
h
o
l
o
g
y
.
IEE
E
T
ra
n
sa
c
ti
o
n
s
o
n
Pa
tt
e
rn
A
n
a
lys
is
a
n
d
M
a
c
h
i
n
e
In
telli
g
e
n
c
e
.
1
9
8
7
;
4
:
5
3
2
-
5
5
0
.
[2
3
]
B.
Ka
u
r,
a
n
d
A
.
G
a
rg
.
Co
m
p
a
r
a
ti
v
e
stu
d
y
o
f
d
i
ff
e
r
e
n
t
e
d
g
e
d
e
tec
ti
o
n
tec
h
n
i
q
u
e
s.
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
En
g
i
n
e
e
rin
g
S
c
ien
c
e
a
n
d
T
e
c
h
n
o
l
o
g
y
(
IJ
ES
T
).
2
0
1
1
:
3
.
[2
4
]
R.
Ka
u
r,
a
n
d
S
.
Ka
u
r.
Ob
jec
t
E
x
trac
ti
o
n
a
n
d
Bo
u
n
d
a
ry
T
r
a
c
in
g
A
lg
o
rit
h
m
s
f
o
r
Dig
it
a
l
Im
a
g
e
P
r
o
c
e
ss
in
g
:
Co
m
p
a
ra
ti
v
e
A
n
a
l
y
sis:
A
Re
v
ie
w
.
In
ter
n
a
ti
o
n
a
l
J
o
u
rn
a
l
o
f
Ad
v
a
n
c
e
d
Res
e
a
rc
h
i
n
Co
mp
u
ter
S
c
ien
c
e
a
n
d
S
o
ft
w
a
re
En
g
in
e
e
rin
g
.
2
0
1
3
;
3
(
5
)
:
6
.
[2
5
]
P
.
P
e
ro
n
a
,
T
.
S
h
i
o
ta,
a
n
d
J.
M
a
li
k
.
A
n
iso
tro
p
ic
d
if
f
u
sio
n
.
Ge
o
me
try
-
d
riv
e
n
d
if
fu
si
o
n
in
c
o
m
p
u
ter
v
isio
n
.
S
p
rin
g
e
r.
1
9
9
4
:
7
3
-
9
2
.
[2
6
]
C.
T
sio
tsio
s,
a
n
d
M
.
P
e
tro
u
.
On
th
e
c
h
o
ice
o
f
th
e
p
a
ra
m
e
t
e
rs
f
o
r
a
n
iso
tro
p
ic
d
if
f
u
sio
n
in
im
a
g
e
p
ro
c
e
ss
in
g
.
Pa
tt
e
rn
re
c
o
g
n
it
i
o
n
.
2
0
1
3
;
4
6
(
5
):
1
3
6
9
-
1
3
8
1
.
[2
7
]
K.
S
e
sh
a
d
rin
a
th
a
n
,
R.
S
o
u
n
d
a
ra
ra
jan
,
A
.
Bo
v
ik
,
a
n
d
L
.
Co
rm
a
c
k
.
L
IV
E
v
id
e
o
q
u
a
li
ty
d
a
tab
a
se
.
La
b
o
ra
to
ry
f
o
r
Im
a
g
e
a
n
d
V
id
e
o
En
g
i
n
e
e
rin
g
.
2
0
0
9
.
[2
8
]
K.
S
e
sh
a
d
ri
n
a
th
a
n
,
R.
S
o
u
n
d
a
ra
ra
jan
,
A
.
C.
Bo
v
ik
,
a
n
d
L
.
K.
C
o
rm
a
c
k
.
S
tu
d
y
o
f
S
u
b
jec
ti
v
e
a
n
d
Ob
jec
ti
v
e
Qu
a
li
ty
A
ss
e
ss
m
e
n
t
o
f
V
i
d
e
o
.
IE
EE
T
ra
n
sa
c
ti
o
n
s
o
n
Im
a
g
e
Pr
o
c
e
ss
in
g
.
2
0
1
0
;
1
9
(6
):
1
4
2
7
-
1
4
4
1
.
[2
9
]
K.
S
e
sh
a
d
rin
a
t
h
a
n
,
R.
S
o
u
n
d
a
ra
r
a
jan
,
A
.
C.
Bo
v
ik
,
a
n
d
L
.
K.
Co
rm
a
c
k
.
A
su
b
jec
ti
v
e
stu
d
y
to
e
v
a
lu
a
te
v
id
e
o
q
u
a
li
ty
a
ss
e
ss
m
e
n
t
a
lg
o
rit
h
m
s.
IS
&
T
/S
P
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.
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