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1.
I
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[
1
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,
[
2
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.
H
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t
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[
3
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.
L
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p
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4
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[
5
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.
T
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tan
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Hig
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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t J E
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&
C
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I
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N:
2088
-
8
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N
o
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l te
ch
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iq
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to
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h
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…
(
P
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)
2315
p
r
eser
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lt
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[
6
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.
Ov
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all,
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tio
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p
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eser
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[
7
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.
T
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,
in
clu
d
in
g
m
o
tio
n
b
lu
r
in
d
u
ce
d
b
y
ca
m
er
a
o
r
o
b
ject
m
o
v
e
m
en
t,
d
ef
o
cu
s
b
lu
r
r
esu
ltin
g
f
r
o
m
im
p
r
o
p
er
f
o
c
u
s
s
ettin
g
s
,
o
r
len
s
ab
er
r
atio
n
s
th
at
d
is
to
r
t
th
e
ca
p
tu
r
ed
s
ce
n
e
.
Mo
r
eo
v
er
,
im
ag
es
m
ay
ex
h
i
b
it
a
co
m
b
in
atio
n
o
f
th
ese
b
lu
r
ty
p
es,
f
u
r
th
er
co
m
p
licatin
g
th
e
task
o
f
d
esig
n
in
g
r
o
b
u
s
t
b
lu
r
d
etec
tio
n
m
eth
o
d
s
[
8
]
.
C
o
n
s
eq
u
en
tly
,
ex
ten
s
iv
e
r
esear
ch
h
as
f
o
cu
s
ed
o
n
d
ev
elo
p
in
g
d
iv
er
s
e
tec
h
n
iq
u
es
to
ac
c
u
r
ately
id
e
n
tif
y
an
d
class
if
y
b
l
u
r
,
u
tili
zin
g
m
eth
o
d
s
s
u
ch
as m
ac
h
in
e
lear
n
in
g
,
f
r
e
q
u
en
c
y
d
o
m
a
in
an
aly
s
is
an
d
ed
g
e
d
etec
tio
n
.
Sig
n
if
ican
t
ad
v
an
ce
m
en
ts
i
n
b
lu
r
d
etec
tio
n
tec
h
n
o
lo
g
ies
h
av
e
b
ee
n
lar
g
ely
d
r
iv
en
b
y
t
h
e
u
s
e
o
f
co
n
v
o
l
u
tio
n
al
n
eu
r
al
n
etwo
r
k
s
.
E
ar
ly
tech
n
iq
u
es,
s
u
ch
as
th
o
s
e
b
y
Vijay
[
9
]
u
tili
ze
d
co
n
v
o
lu
tio
n
al
n
eu
r
al
n
etwo
r
k
s
(
C
NNs)
f
o
r
g
e
n
er
a
l
im
ag
e
d
eb
lu
r
r
in
g
,
s
ettin
g
a
p
r
ec
ed
e
n
t
f
o
r
m
o
r
e
tar
g
et
ed
ap
p
r
o
ac
h
es.
B
y
in
tr
o
d
u
cin
g
an
e
n
s
em
b
le
C
NN
ap
p
r
o
ac
h
with
p
r
u
n
ed
v
er
s
io
n
s
o
f
Alex
Net
an
d
Go
o
g
leN
et,
W
an
g
et
a
l.
[
1
0
]
d
em
o
n
s
tr
ated
a
s
ig
n
i
f
ican
t
e
n
h
an
ce
m
en
t
in
class
if
y
in
g
v
a
r
i
o
u
s
b
lu
r
ty
p
es
co
m
p
ar
ed
to
tr
ad
itio
n
al
m
eth
o
d
s
.
Kim
et
a
l.
[
1
1
]
em
p
lo
y
e
d
a
d
ee
p
en
co
d
er
-
d
ec
o
d
er
n
etwo
r
k
with
m
u
lti
-
s
ca
le
f
ea
tu
r
es
to
ef
f
ec
tiv
ely
d
etec
t
d
ef
o
cu
s
a
n
d
m
o
tio
n
b
lu
r
.
Hu
an
g
an
d
Xia
[
5
]
f
u
r
th
e
r
ad
v
a
n
ce
d
th
e
f
ield
with
a
jo
in
t
m
eth
o
d
th
at
co
m
b
in
es
b
lu
r
k
e
r
n
el
esti
m
atio
n
with
C
NN
-
b
ased
d
ec
o
n
v
o
lu
tio
n
,
s
ig
n
if
ican
tly
im
p
r
o
v
in
g
im
a
g
e
r
esto
r
atio
n
q
u
ality
.
R
ec
en
t
ev
alu
atio
n
s
b
y
Pag
ad
u
an
et
a
l.
[
1
2
]
h
av
e
p
r
o
v
id
ed
in
s
ig
h
ts
in
to
th
e
ef
f
ec
tiv
e
n
e
s
s
o
f
d
if
f
er
e
n
t
b
l
u
r
d
etec
tio
n
tech
n
iq
u
es,
lead
in
g
t
o
th
e
d
ev
elo
p
m
en
t
o
f
s
o
p
h
is
ticated
m
o
d
els
s
u
ch
as
th
e
p
y
r
a
m
id
m
-
s
h
ap
ed
d
ee
p
n
eu
r
al
n
etwo
r
k
(
PM
-
Net)
b
y
W
an
g
et
a
l.
[
1
3
]
,
wh
ich
en
h
an
ce
s
b
o
th
ac
cu
r
ac
y
an
d
s
p
ee
d
in
b
lu
r
d
etec
tio
n
,
a
n
d
th
e
m
u
lti
-
s
ca
le
d
ilated
U
-
Net
m
o
d
el
b
y
Xiao
et
a
l.
[
1
4
]
,
wh
ich
in
teg
r
ates
m
u
lti
-
s
ca
le
f
ea
tu
r
es
f
o
r
s
u
p
er
i
o
r
d
etec
tio
n
p
er
f
o
r
m
an
ce
.
ML
an
d
n
eu
r
al
n
etwo
r
k
s
ar
e
p
o
wer
f
u
l
tech
n
iq
u
es
u
s
ed
f
o
r
class
if
icatio
n
task
s
u
s
ed
in
m
an
y
ap
p
licatio
n
s
[
1
5
]
–
[
1
7
]
I
m
a
g
e
d
e
b
l
u
r
r
i
n
g
t
e
c
h
n
o
l
o
g
y
h
a
s
e
v
o
l
v
e
d
s
i
g
n
i
f
i
c
a
n
tl
y
i
n
v
a
r
i
o
u
s
i
m
a
g
i
n
g
a
p
p
li
c
a
ti
o
n
s
f
r
o
m
i
m
a
g
e
s
u
r
v
e
i
l
l
a
n
ce
t
o
m
e
d
i
c
al
i
m
a
g
i
n
g
u
s
i
n
g
r
e
ce
n
t
t
e
c
h
n
i
q
u
e
s
[
1
8
]
.
L
i
e
t
a
l
.
[
1
9
]
d
e
v
e
l
o
p
e
d
a
m
o
d
u
l
e
u
s
i
n
g
t
h
e
g
r
a
y
l
e
v
e
l
c
o
-
o
c
c
u
r
r
e
n
c
e
m
a
t
r
i
x
(
GL
C
M
)
t
o
i
m
p
r
o
v
e
t
e
x
t
u
r
e
p
r
es
e
r
v
a
t
i
o
n
i
n
d
e
b
l
u
r
r
e
d
i
m
a
g
es
,
c
r
u
c
i
a
l
f
o
r
d
i
g
i
t
al
p
h
o
t
o
g
r
a
p
h
y
a
n
d
v
i
s
i
o
n
s
y
s
t
em
s
.
W
a
n
g
e
t
a
l
.
[
2
0
]
one
-
s
te
p
C
N
N
m
e
t
h
o
d
f
u
r
t
h
e
r
a
d
v
a
n
c
e
d
t
h
e
f
i
e
l
d
b
y
e
f
f
e
c
t
i
v
e
l
y
r
es
t
o
r
i
n
g
b
l
u
r
r
y
f
a
ce
i
m
a
g
e
s
,
b
e
n
e
f
i
t
i
n
g
f
a
c
ia
l
r
e
co
g
n
i
t
i
o
n
t
e
c
h
n
o
l
o
g
i
e
s
.
P
e
n
g
e
t
a
l
.
[
2
1
]
i
n
t
e
g
r
a
t
e
d
d
e
b
l
u
r
r
i
n
g
w
i
t
h
f
e
a
t
u
r
e
-
b
as
e
d
s
p
a
r
s
e
r
e
p
r
es
e
n
t
at
i
o
n
,
e
n
h
a
n
c
i
n
g
b
o
t
h
i
m
a
g
e
c
l
a
r
it
y
a
n
d
m
a
t
c
h
i
n
g
a
c
c
u
r
a
c
y
.
Z
h
a
n
g
e
t
a
l
.
[
2
2
]
c
o
m
b
i
n
e
d
d
e
b
l
u
r
r
i
n
g
w
i
t
h
s
u
p
e
r
-
r
es
o
l
u
t
io
n
t
h
r
o
u
g
h
a
t
t
e
n
t
i
o
n
d
u
a
l
s
u
p
e
r
v
i
s
e
d
n
e
tw
o
r
k
s
,
i
m
p
r
o
v
i
n
g
h
i
g
h
-
r
e
s
o
l
u
t
i
o
n
i
m
a
g
i
n
g
,
p
a
r
t
i
c
u
l
a
r
l
y
i
n
m
e
d
i
c
a
l
a
n
d
s
a
t
e
l
l
it
e
a
p
p
l
i
c
at
i
o
n
s
.
Fi
n
a
l
ly
,
C
h
o
w
d
h
u
r
y
e
t
a
l
.
[
2
3
]
a
d
d
r
e
s
s
e
d
P
o
i
s
s
o
n
n
o
i
s
e
a
n
d
b
l
u
r
i
n
s
c
i
e
n
t
i
f
i
c
i
m
a
g
i
n
g
w
i
t
h
f
r
a
c
t
i
o
n
a
l
-
o
r
d
e
r
t
o
t
a
l
v
a
r
ia
t
i
o
n
r
e
g
u
l
a
r
i
z
a
t
i
o
n
,
c
r
u
c
i
a
l
f
o
r
f
i
e
l
d
s
li
k
e
a
s
t
r
o
n
o
m
y
a
n
d
b
i
o
l
o
g
y
.
T
h
e
s
e
i
n
n
o
v
a
t
i
o
n
s
r
e
f
l
ec
t
a
t
r
e
n
d
t
o
w
a
r
d
s
m
o
r
e
t
a
i
l
o
r
e
d
a
n
d
e
f
f
e
c
t
i
v
e
d
e
b
l
u
r
r
i
n
g
s
o
l
u
t
i
o
n
s
ac
r
o
s
s
d
i
v
e
r
s
i
f
i
e
d
d
o
m
a
i
n
s
.
B
lu
r
d
etec
tio
n
a
n
d
d
eb
lu
r
te
ch
n
iq
u
es
h
av
e
m
ad
e
n
o
tab
le
ad
v
an
c
em
en
ts
in
r
ec
en
t
y
ea
r
s
b
u
t
s
till
g
r
ap
p
le
with
s
ev
er
al
ch
allen
g
es.
Acc
u
r
ate
b
lu
r
d
etec
tio
n
is
ch
allen
g
in
g
d
u
e
to
th
e
v
ar
y
in
g
ty
p
es
an
d
d
eg
r
ee
s
o
f
b
lu
r
,
n
o
is
e
in
ter
f
er
en
ce
,
an
d
th
e
p
r
esen
ce
o
f
tex
t
u
r
es
th
at
m
ig
h
t
b
e
m
is
tak
en
f
o
r
b
lu
r
.
Deb
lu
r
r
in
g
r
esear
c
h
f
ac
es
ch
allen
g
es
s
u
ch
as
h
an
d
lin
g
v
ar
i
o
u
s
ty
p
es
o
f
b
lu
r
s
(
m
o
tio
n
,
d
ef
o
cu
s
,
an
d
Ga
u
s
s
ian
)
,
ac
cu
r
ately
esti
m
atin
g
n
o
n
-
u
n
if
o
r
m
b
lu
r
k
er
n
els,
an
d
b
alan
cin
g
co
m
p
u
tatio
n
al
co
m
p
lex
ity
with
a
r
tifa
ct
s
u
p
p
r
ess
io
n
.
Ad
d
itio
n
ally
,
d
ee
p
lear
n
in
g
a
p
p
r
o
ac
h
es
b
r
in
g
is
s
u
es
lik
e
th
e
n
ee
d
f
o
r
lar
g
e
t
r
ain
in
g
d
a
tasets
an
d
en
s
u
r
in
g
m
o
d
el
g
e
n
er
aliza
tio
n
ac
r
o
s
s
d
iv
er
s
e
r
ea
l
-
wo
r
ld
c
o
n
d
itio
n
s
.
T
h
is
r
esear
ch
f
o
cu
s
es
o
n
f
o
llo
win
g
o
b
jectiv
es:
i)
d
ev
el
o
p
i
n
g
m
o
r
e
r
o
b
u
s
t
an
d
g
en
e
r
alize
d
m
o
d
els
th
at
ca
n
h
an
d
le
d
i
v
er
s
e
ty
p
es
o
f
b
lu
r
s
,
ii)
r
ed
u
cin
g
c
o
m
p
u
ta
tio
n
al
co
m
p
lex
ity
to
e
n
ab
le
r
e
al
-
tim
e
ap
p
licatio
n
s
s
u
ch
an
cien
t
im
a
g
e
r
esto
r
atio
n
,
iii)
c
o
m
b
in
in
g
b
lu
r
d
etec
tio
n
an
d
d
eb
lu
r
r
in
g
in
to
a
s
in
g
le
u
n
if
ied
f
r
am
ewo
r
k
f
o
r
m
o
r
e
e
f
f
icien
t
p
r
o
ce
s
s
in
g
,
an
d
iv
)
e
x
p
lo
r
in
g
t
h
e
u
s
e
o
f
n
ew
ar
ch
itectu
r
es
an
d
tr
ain
in
g
tech
n
iq
u
es
in
d
ee
p
lear
n
in
g
to
f
u
r
th
e
r
en
h
an
ce
p
er
f
o
r
m
a
n
ce
.
T
h
is
p
a
p
er
is
o
r
g
an
ized
as
f
o
llo
ws:
th
e
in
tr
o
d
u
ctio
n
is
g
iv
e
n
in
s
ec
tio
n
1
,
th
e
s
u
g
g
ested
m
eth
o
d
o
lo
g
y
is
d
escr
ib
ed
in
s
ec
tio
n
2
,
an
d
th
e
ex
p
er
im
en
tal
s
etu
p
,
r
esu
lts
,
an
d
d
is
cu
s
s
io
n
ar
e
p
r
esen
ted
in
s
ec
tio
n
3
.
Fin
ally
,
t
h
e
co
n
cl
u
s
io
n
is
p
r
o
v
id
ed
i
n
s
ec
tio
n
4
.
2.
M
E
T
H
O
D
R
esto
r
in
g
an
cien
t
im
ag
es
is
v
ital
f
o
r
p
r
eser
v
in
g
o
u
r
s
h
ar
ed
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ltu
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al
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er
itag
e,
o
f
f
er
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g
g
li
m
p
s
es
in
to
th
e
p
ast,
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d
en
r
ich
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n
g
o
u
r
u
n
d
er
s
tan
d
in
g
o
f
h
is
to
r
y
.
Fig
u
r
e
1
o
u
tlin
es
th
e
f
lo
w
o
f
t
h
e
b
lu
r
d
etec
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a
n
d
d
eb
lu
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r
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n
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iq
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e.
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h
e
“
H
is
to
r
ical
p
lace
s
d
ataset
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f
Pu
n
e
”
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u
s
ed
as
th
e
an
cien
t
im
ag
e
d
ataset
f
o
r
th
is
ap
p
r
o
ac
h
.
T
h
e
d
ataset
s
p
an
s
v
ar
io
u
s
ca
teg
o
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ies
as
“
Om
k
ar
esh
war
Ma
n
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“
Sh
an
iwar
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ad
a
,
”
“
Kasab
a
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ap
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Ma
n
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ir
,
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“
Par
v
ati
,
”
“
L
al
Ma
h
al
,
”
an
d
“
T
u
lash
ib
au
g
R
am
Ma
n
d
ir
”
[
2
4
]
.
T
h
is
d
ataset
g
en
er
ates
d
eg
r
ad
e
d
im
ag
es
f
o
r
m
o
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el
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u
ild
in
g
b
y
ad
d
in
g
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ar
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u
s
t
y
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es
o
f
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lu
r
s
.
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h
ese
d
eg
r
a
d
ed
im
ag
es
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n
d
er
g
o
m
u
ltip
le
lev
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im
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e
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e
g
r
ad
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etec
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d
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r
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s
s
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g
,
f
ea
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e
x
tr
ac
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d
n
e
u
r
al
n
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if
icatio
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h
en
id
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tifie
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ty
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e
o
f
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r
u
tili
ze
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f
o
r
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e
s
u
b
s
eq
u
en
t
d
eb
lu
r
r
in
g
p
r
o
ce
s
s
to
r
esto
r
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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8
I
n
t J E
lec
&
C
o
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p
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n
g
,
Vo
l.
15
,
No
.
2
,
Ap
r
il
20
25
:
2
3
1
4
-
2
3
2
4
2316
th
e
im
ag
es.
Fin
ally
,
p
er
f
o
r
m
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ce
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aly
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is
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u
cted
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s
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ig
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u
ar
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r
(
MSE
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d
s
tr
u
ctu
r
al
s
im
ilar
ity
in
d
ex
(
SS
I
M)
m
etr
ics.
Fig
u
r
e
1
.
Flo
w
f
o
r
b
l
u
r
d
e
te
cti
o
n
an
d
d
eb
l
u
r
p
r
o
ce
s
s
2
.
1
.
Arc
hite
ct
ure
f
o
r
blu
r
identif
ica
t
io
n
T
h
e
ar
ch
itectu
r
e
f
o
r
b
lu
r
id
en
tific
atio
n
,
illu
s
tr
ated
in
Fig
u
r
e
2
,
d
ete
r
m
in
es
th
e
s
p
ec
if
ic
d
e
g
r
ad
atio
n
ty
p
e
an
d
f
ac
ilit
ates
th
e
r
esto
r
atio
n
o
f
d
eg
r
ad
e
d
im
a
g
es
a
cc
o
r
d
in
g
l
y
.
A
d
eg
r
ad
ed
im
a
g
e
is
in
p
u
t
f
o
r
t
h
is
id
en
tific
atio
n
p
r
o
ce
s
s
wh
ich
is
g
en
er
ated
th
r
o
u
g
h
m
ix
in
g
b
lu
r
in
t
h
e
o
r
ig
in
al
im
a
g
e.
Featu
r
e
ex
tr
ac
tio
n
,
esp
ec
ially
u
s
in
g
wav
elet
tr
an
s
f
o
r
m
,
is
cr
u
cial
in
n
e
u
r
al
n
etwo
r
k
s
as
it
r
ed
u
ce
s
d
ata
d
im
en
s
io
n
ality
an
d
ca
p
tu
r
es
im
p
o
r
tan
t
p
atter
n
.
T
h
is
ap
p
r
o
ac
h
b
o
o
s
ts
th
e
n
etwo
r
k
'
s
ef
f
icien
cy
,
ac
cu
r
ac
y
,
an
d
g
en
er
aliza
tio
n
b
y
f
o
cu
s
in
g
o
n
th
e
m
o
s
t
r
elev
an
t
f
ea
tu
r
es.
T
h
e
wav
elet
tr
an
s
f
o
r
m
is
co
m
m
o
n
ly
em
p
lo
y
ed
f
o
r
f
ea
tu
r
e
ex
tr
ac
tio
n
,
with
r
esu
ltin
g
f
ea
tu
r
es th
en
f
e
d
in
to
a
n
eu
r
al
n
etwo
r
k
f
o
r
cla
s
s
if
icatio
n
.
Fig
u
r
e
2
.
B
lu
r
id
e
n
tific
atio
n
ar
ch
itectu
r
e
Fu
r
th
er
,
th
ese
ex
tr
ac
ted
f
ea
t
u
r
es
ar
e
p
r
o
ce
s
s
ed
th
r
o
u
g
h
th
e
co
n
v
o
l
u
tio
n
/
r
ec
tifie
d
lin
ea
r
u
n
it
(
R
eL
U)
lay
er
o
f
C
NN.
T
h
e
m
ain
aim
o
f
th
e
co
n
v
o
lu
tio
n
/R
eL
U
lay
er
is
to
in
tr
o
d
u
ce
th
e
n
o
n
-
lin
ea
r
ity
an
d
to
s
o
lv
e
th
e
is
s
u
e
r
elate
d
to
t
h
e
v
an
is
h
in
g
g
r
ad
ie
n
t.
Her
e,
we
h
av
e
co
n
s
id
er
ed
th
e
n
eg
ativ
e
v
alu
es
also
with
a
n
eg
ativ
e
s
lo
p
e
to
it.
T
h
e
PR
eL
U
f
u
n
ctio
n
is
as g
iv
en
in
(
1
)
.
(
)
=
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0
,
)
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0
,
)
(
1
)
wh
er
e
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e
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le
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ar
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eter
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d
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es
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h
e
p
ar
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eter
M
lear
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s
b
y
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s
in
g
b
ac
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r
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p
a
g
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at
a
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c
r
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th
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s
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ai
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(
,
(
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{
1
2
(
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(
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2
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)
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|
−
1
2
2
ℎ
(
2
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J E
lec
&
C
o
m
p
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n
g
I
SS
N:
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N
o
ve
l te
ch
n
iq
u
e
to
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eb
lu
r
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in
g
a
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b
l
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(
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n
a
m
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a
w
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r
)
2317
wh
er
e
is
th
e
b
ac
k
p
r
o
p
ag
atio
n
f
u
n
ctio
n
th
at
d
ep
en
d
s
o
n
an
d
(
)
.
(
d
elta)
is
th
e
s
m
all
am
o
u
n
t
o
f
ch
an
g
e
t
h
at
o
cc
u
r
r
ed
in
t
h
e
weig
h
t’
s
ad
ju
s
tm
en
t
.
is
th
e
ch
an
g
es
in
weig
h
ts
th
at
tr
ac
k
ed
in
t
h
e
f
o
r
war
d
d
ir
ec
tio
n
.
(
)
is
th
e
ch
an
g
es in
w
eig
h
ts
th
at
tr
ac
k
ed
in
th
e
b
ac
k
war
d
d
ir
ec
tio
n
.
T
h
e
eq
u
atio
n
co
n
s
o
lid
ates
MSE
an
d
MA
E
with
d
ep
en
d
en
cy
o
n
an
o
th
er
p
ar
am
eter
ca
lled
d
elta.
I
f
th
e
d
elta
is
h
ig
h
,
th
e
lo
s
s
f
u
n
ctio
n
wo
r
k
s
as
an
MSE
;
if
th
e
d
elta
is
lo
w,
th
e
n
t
h
e
lo
s
s
f
u
n
ctio
n
wo
r
k
s
as
an
MA
E
.
As
th
e
f
in
al
o
u
tco
m
e
th
e
C
NN
d
eter
m
in
es
wh
eth
er
th
e
d
eg
r
ad
e
d
im
ag
e
is
af
f
ec
ted
b
y
d
ef
o
c
u
s
,
b
ilater
al,
g
au
s
s
ian
,
m
ed
ian
,
o
r
m
o
tio
n
b
lu
r
.
2
.
2
.
Arc
hite
ct
ure
f
o
r
deblu
r
t
ec
hn
iqu
e
Af
ter
d
etec
tin
g
t
h
e
ty
p
e
o
f
b
lu
r
n
ex
t
p
r
o
ce
s
s
s
tar
ts
f
o
r
th
e
d
e
b
lu
r
tech
n
iq
u
e.
T
h
e
d
eb
lu
r
ar
c
h
itectu
r
e
is
s
h
o
wn
in
Fig
u
r
e
3
.
T
h
e
ap
p
r
o
ac
h
o
f
p
atch
ex
tr
ac
tio
n
an
d
n
o
n
-
lin
ea
r
m
ap
p
in
g
f
o
r
r
esto
r
atio
n
an
d
d
etailin
g
in
v
o
lv
es
s
ev
er
al
k
e
y
s
tep
s
aim
ed
at
en
h
a
n
cin
g
t
h
e
q
u
ality
an
d
f
id
elity
o
f
im
a
g
es.
Firstl
y
,
p
atch
e
x
tr
ac
tio
n
in
v
o
lv
es
d
iv
id
in
g
th
e
in
p
u
t
im
ag
e
in
to
s
m
aller
,
o
v
e
r
lap
p
i
n
g
r
eg
io
n
s
o
r
p
atch
es.
T
h
is
p
r
o
ce
s
s
allo
ws
f
o
r
a
m
o
r
e
lo
ca
lized
an
aly
s
is
an
d
m
an
ip
u
latio
n
o
f
im
ag
e
f
ea
tu
r
es,
f
ac
ilit
atin
g
tar
g
eted
r
esto
r
atio
n
an
d
d
etailin
g
.
Fo
llo
win
g
p
atch
ex
tr
ac
tio
n
,
a
n
o
n
-
lin
ea
r
m
a
p
p
in
g
tech
n
iq
u
e
is
ap
p
lied
to
ea
ch
p
atch
.
N
o
n
-
lin
ea
r
m
a
p
p
in
g
m
eth
o
d
s
en
a
b
le
m
o
r
e
s
o
p
h
is
ti
ca
ted
tr
an
s
f
o
r
m
atio
n
s
o
f
p
ix
el
v
alu
es,
allo
win
g
f
o
r
th
e
e
n
h
a
n
ce
m
en
t
o
f
im
ag
e
d
etails
an
d
r
esto
r
atio
n
o
f
lo
s
t
in
f
o
r
m
atio
n
.
T
h
ese
m
ap
p
in
g
s
o
f
ten
in
v
o
lv
e
co
m
p
lex
m
at
h
em
atica
l
f
u
n
ctio
n
s
th
at
ef
f
ec
tiv
ely
ad
j
u
s
t p
ix
el
v
a
lu
es b
ased
o
n
lo
ca
l im
a
g
e
ch
ar
ac
ter
is
tics
.
Fig
u
r
e
3
.
Deb
l
u
r
ar
c
h
itectu
r
e
2.
2
.
1
.
P
a
t
ch
ex
t
ra
ct
i
o
n
T
h
e
in
itial
p
h
ase
em
p
lo
y
s
1
2
8
f
ilter
s
s
ized
9
×
9
×
3
f
o
r
th
e
win
d
o
w'
s
p
atch
ex
tr
ac
tio
n
.
I
t
p
r
o
ce
s
s
es
ex
tr
ac
ted
im
a
g
e
p
atch
es
X
u
s
in
g
1
2
8
f
ilter
s
W1
an
d
b
iases
B1
.
T
h
e
s
elec
tio
n
o
f
th
ese
weig
h
ts
W1
is
ad
ap
ted
b
ased
o
n
t
h
e
ty
p
e
o
f
b
lu
r
i
d
en
tifie
d
in
th
e
in
itial
s
tag
e,
allo
win
g
th
e
n
e
u
r
al
n
etwo
r
k
to
f
o
cu
s
o
n
s
p
ec
if
ic
b
l
u
r
ch
ar
ac
ter
is
tics
with
in
lo
ca
lize
d
p
atch
es.
T
h
is
ap
p
r
o
ac
h
im
p
r
o
v
es th
e
n
etwo
r
k
'
s
ab
ilit
y
to
d
if
f
er
en
tiate
b
etwe
en
b
lu
r
r
ed
an
d
s
h
ar
p
r
eg
io
n
s
,
lea
d
in
g
to
m
o
r
e
ac
cu
r
ate
p
r
ed
icti
o
n
s
.
T
h
e
e
x
p
r
ess
io
n
f
o
r
th
e
n
e
u
r
al
n
etwo
r
k
'
s
f
ir
s
t
lay
er
is
d
ef
in
ed
as
(
3
)
:
1
(
)
=
1
×
+
1
(
3
)
wh
e
r
e
d
en
o
tes th
e
im
a
g
e
,
1
r
ep
r
esen
ts
th
e
1
2
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ic
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f
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im
a
g
e
p
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ce
s
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in
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task
[
3
2
]
–
[
3
4
]
.
T
h
e
p
er
f
o
r
m
a
n
ce
o
f
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y
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PS
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.
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Ga
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h
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5
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5
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an
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at
with
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it
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f
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ch
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ly
3
m
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as sh
o
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in
T
ab
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5
[
3
5
]
.
82.7
3
83.4
6
94
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97.7
4
96.9
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98.1
3
75
80
85
90
95
100
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I
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2088
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(
P
o
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n
a
m
P
a
w
a
r
)
2321
T
ab
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4
.
PS
NR
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MSE
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Fig
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7
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ith
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3
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9
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9
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.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
7
0
8
I
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t J E
lec
&
C
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m
p
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g
,
Vo
l.
15
,
No
.
2
,
Ap
r
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20
25
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2
3
1
4
-
2
3
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4
2322
T
ab
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6
.
Deb
lu
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P
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(
d
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[
3
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2
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2
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[
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NC
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[
1
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L.
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H
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a
,
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Jo
i
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b
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[
6
]
J.
C
a
o
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Y
.
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a
,
M
.
Y
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n
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n
d
X
.
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a
n
,
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[
7
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I
.
A
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z
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T.
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.
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.
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.
,
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m
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[
9
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R
.
V
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N:
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