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i
n
g
pr
o
m
i
s
i
ng
r
e
s
u
l
t
s
f
o
r
i
m
a
g
e
f
u
s
i
o
n
,
[
5]
,
[
26
]
,
[
27
]
,
[
32
]
,
[
33]
t
h
e
w
a
v
e
l
e
t
t
r
a
n
s
f
o
r
m
c
o
n
t
r
i
b
ut
e
s
to
o
b
t
a
i
ni
ng
b
e
t
t
e
r
f
us
e
d
im
a
ge
s
du
e
t
o
t
h
e
wa
y
i
n
w
hi
c
h
c
o
e
f
f
i
c
i
e
n
t
s
a
r
e
c
o
m
put
e
d
a
s
pa
r
t
o
f
t
h
e
t
r
a
n
s
f
o
r
m
a
t
i
o
n
pr
o
c
e
s
s
[
34
]
,
[
35]
.
T
hi
s
pr
o
c
e
s
s
y
i
e
l
d
s
t
h
e
wa
v
e
l
e
t
p
l
a
n
e
s
,
w
hi
c
h
ke
e
p
m
o
r
e
s
pa
t
i
a
l
a
n
d
s
pe
c
tr
a
l
i
nf
or
m
a
t
i
o
n
f
r
o
m
t
h
e
or
i
g
i
n
a
l
i
m
a
ge
s
t
h
a
n
ot
h
e
r
tec
h
ni
que
s
.
W
a
v
e
l
e
t
-
b
a
s
e
d
t
e
c
h
ni
q
ue
s
a
l
s
o
p
r
od
uc
e
a
n
i
n
ten
s
i
t
y
c
o
m
p
o
n
e
n
t
t
h
a
t
m
a
i
n
ta
i
n
s
t
h
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s
p
a
t
i
a
l
r
i
c
h
n
e
s
s
o
f
i
m
a
ge
s
a
l
o
n
g
wi
t
h
ton
e
a
n
d
s
a
tu
r
a
t
i
o
n
c
o
m
p
o
n
e
n
t
s
th
a
t
th
a
t
m
a
i
n
t
a
i
n
s
pe
c
tr
a
l
r
i
c
hn
e
s
s
wh
e
n
tr
a
n
s
f
or
m
in
g
t
h
e
i
m
a
ge
c
o
m
p
o
s
i
t
i
o
n
f
r
o
m
R
G
B
to
I
H
S
[
36
]
.
T
h
e
pr
e
s
e
n
t
wo
r
k
f
o
c
us
e
s
o
n
s
i
x
s
a
t
e
l
li
t
e
-
im
a
ge
f
us
i
o
n
m
e
t
h
o
ds
,
n
a
m
e
ly
t
h
e
w
a
v
e
l
e
t
2D
-
M
t
r
a
n
s
f
o
r
m
us
i
ng
t
h
e
R
GB
-
to
-
H
S
V
c
o
l
o
r
m
o
de
l
[
37]
,
t
h
e
gr
a
m
s
c
hm
i
dt
(G
-
S
)
m
e
t
h
o
d
,
hi
g
h
-
f
r
e
que
n
c
y
m
o
du
l
a
t
i
o
n
(
HF
M
)
,
hi
g
h
pa
s
s
f
il
t
e
r
t
r
a
n
s
f
o
r
m
(
H
P
F
)
,
s
i
m
p
l
e
m
e
a
n
v
a
l
ue
(
S
M
V
)
,
a
n
d
pr
i
nc
i
pa
l
c
o
m
po
n
e
n
t
a
n
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ly
s
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(
P
C
A
)
.
A
s
t
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p
-
by
-
s
t
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p
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m
p
l
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m
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t
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p
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f
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ppl
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a
c
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m
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ds
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M
o
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a
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nc
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f
r
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f
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im
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M
U
L
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I
W
a
v
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2
D
-
M
,
M
UL
T
I
G
-
S
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M
U
L
T
I
M
H
F
,
M
UL
T
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H
P
F
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M
UL
T
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S
M
V
,
y
M
UL
T
I
P
CA
)
i
n
t
e
r
m
s
o
f
s
pe
c
i
f
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c
n
u
m
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r
i
a
l
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nde
x
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s
,
n
a
m
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ly
t
h
e
c
o
r
r
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l
a
t
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o
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c
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f
f
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c
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t
,
t
h
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a
t
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pe
c
t
r
a
l
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r
r
o
r
(
R
A
S
E
)
i
nde
x
,
t
h
e
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r
r
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ur
r
e
l
a
t
i
ve
g
l
o
ba
l
e
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d
im
e
n
s
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nn
e
ll
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de
s
y
n
t
he
s
e
(
E
R
G
A
S
)
i
n
de
x
,
a
n
d
t
h
e
Q
u
ni
ve
r
s
a
l
qua
li
t
y
i
nde
x
.
2.
M
E
T
HO
DOL
OG
Y
T
hi
s
s
e
c
t
i
o
n
i
s
t
h
r
e
e
f
o
l
d:
a
de
s
c
r
i
pt
i
o
n
o
f
t
h
e
s
a
t
e
l
li
t
e
im
a
ge
s
e
m
p
l
o
y
e
d
i
n
t
h
e
s
t
ud
y
i
s
pr
o
vi
de
d
;
f
o
l
l
o
we
d
by
a
de
s
c
r
i
pt
i
o
n
o
f
t
h
e
s
i
x
im
a
ge
-
f
us
i
o
n
m
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t
h
o
ds
,
whi
c
h
i
nc
l
ude
s
a
pr
o
po
s
a
l
f
o
r
i
m
p
l
e
m
e
n
t
i
n
g
t
h
e
m
e
t
h
o
ds
;
f
i
na
ll
y
,
t
he
m
e
t
r
i
c
s
a
pp
li
e
d
t
o
a
s
s
e
s
s
a
n
d
c
o
m
pa
r
e
t
h
e
(
s
p
a
t
i
a
l
a
n
d
s
pe
c
t
r
a
l
)
qua
li
t
y
o
f
t
h
e
r
e
s
u
l
t
i
ng
im
a
ge
s
a
r
e
pr
e
s
e
n
t
e
d.
2
.
1
.
S
a
t
e
l
l
it
e
im
age
s
an
d
t
h
e
r
e
gion
c
ove
r
e
d
T
h
e
r
e
g
i
o
n
c
o
v
e
r
e
d
by
t
h
e
s
a
t
e
l
li
t
e
im
a
ge
s
c
o
r
r
e
s
po
n
ds
to
a
we
s
t
e
r
n
a
r
e
a
o
f
B
o
g
ot
á
(
C
o
l
o
m
bi
a
)
,
s
pe
c
i
f
i
c
a
l
ly
t
h
e
a
r
e
a
a
r
o
un
d
t
h
e
a
i
r
po
r
t
o
f
t
h
e
c
i
t
y
,
n
a
m
e
ly
“
E
l
Do
r
a
do
”
a
i
r
po
r
t
.
T
hi
s
r
e
g
i
o
n
i
s
c
o
v
e
r
e
d
by
I
ko
n
o
s
o
f
s
u
b
-
i
m
a
ge
s
m
u
l
t
i
-
s
pe
c
t
r
a
l
(
M
U
L
T
I
)
o
r
i
g
i
n
a
s
s
h
o
wn
i
n
F
i
gur
e
1
(
a
)
a
n
d
pa
n
c
h
r
o
m
a
t
i
c
(
P
A
N)
a
s
s
h
o
w
n
i
n
F
i
gur
e
1
(
b
)
.
T
h
e
P
A
N
s
u
b
-
i
m
a
ge
h
a
s
a
s
pa
t
i
a
l
r
e
s
o
l
ut
i
o
n
o
f
o
n
e
(
1)
m
e
t
e
r
;
t
hi
s
im
a
ge
wa
s
c
a
pt
ur
e
d
o
n
De
c
e
m
be
r
13
th
,
2007
a
c
c
o
r
di
n
g
t
o
t
h
e
UT
M
/
W
GS
84
r
e
f
e
r
e
nc
e
s
y
s
t
e
m
.
T
he
M
U
L
T
I
s
ub
-
im
a
g
e
i
n
c
l
ude
s
f
o
ur
-
c
h
a
nne
l
i
nf
o
r
m
a
t
i
o
n;
h
o
we
v
e
r
,
o
nly
t
h
r
e
e
c
ha
nn
e
l
s
we
r
e
i
nv
o
l
ve
d
i
n
t
h
e
pr
e
s
e
n
t
s
t
udy
(R
-
r
ed
,
G
-
gr
e
e
n
a
n
d
B
-
bl
ue
)
.
T
h
e
im
a
g
e
h
a
s
a
s
pa
t
i
a
l
r
e
s
o
l
ut
i
o
n
o
f
f
o
ur
(
4)
m
e
t
e
r
s
a
n
d
wa
s
c
a
pt
ur
e
d
o
n
t
h
e
s
a
m
e
da
t
e
a
s
t
h
e
P
A
N
s
u
b
-
im
a
ge
,
a
l
s
o
s
h
a
r
i
ng
t
h
e
s
a
m
e
r
e
f
e
r
e
n
c
e
s
y
s
t
e
m
.
T
h
e
t
wo
i
m
a
ge
s
we
r
e
c
r
o
ppe
d
to
h
a
v
e
a
w
i
dt
h
o
f
2048
pi
xe
l
s
a
n
d
a
h
e
i
g
h
t
o
f
2048
p
i
x
e
l
s
,
s
a
t
i
s
f
yi
ng
d
ya
d
i
c
pr
o
pe
r
t
i
e
s
[
23]
.
(
a
)
(
b
)
F
i
gur
e
1
.
Or
i
g
i
na
l
im
a
ge
s
a
r
e
(
a
)
M
UL
T
I
S
ub
-
i
m
a
ge
a
n
d
(
b
)
P
A
N
s
u
b
-
im
a
ge
;
2048x
2048
p
i
xe
l
s
2
.
2
.
2D
wave
l
e
t
t
r
an
s
f
o
r
m
T
h
e
w
a
v
e
l
e
t
di
s
c
r
e
t
e
tr
a
n
s
f
o
r
m
i
s
a
us
e
f
u
l
too
l
i
n
t
h
e
f
i
e
l
d
o
f
s
i
g
na
l
pr
o
c
e
s
s
i
ng.
T
hi
s
t
r
a
n
s
f
o
r
m
i
s
m
a
i
n
ly
a
pp
li
e
d
t
o
di
vi
de
da
t
a
s
e
t
s
i
n
t
o
s
m
a
l
l
e
r
c
o
m
po
n
e
n
t
s
a
s
s
o
c
i
a
t
e
d
to
di
f
f
e
r
e
n
t
s
pa
t
i
a
l
f
r
e
que
n
c
ies
,
whi
c
h
a
r
e
r
e
pr
e
s
e
n
t
e
d
by
a
c
o
m
m
o
n
s
c
a
l
e
.
Al
go
r
i
t
hm
s
kn
o
w
n
a
s
M
a
ll
a
t
a
n
d
‘
à
t
r
o
us
’
a
r
e
t
y
p
i
c
a
l
i
n
a
pp
lyi
ng
t
h
e
d
i
s
c
r
e
t
e
w
a
v
e
l
e
t
tr
a
n
s
f
o
r
m
t
o
i
m
a
ge
f
us
i
o
n
.
E
a
c
h
o
f
t
h
e
s
e
a
l
go
r
i
t
hm
s
h
a
s
i
t
s
o
wn
m
a
t
h
e
m
a
t
i
c
a
l
pr
o
pe
r
t
i
e
s
a
n
d
l
e
a
d
s
to
a
di
f
f
e
r
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n
t
t
y
p
e
o
f
i
m
a
g
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de
c
o
m
po
s
i
t
i
o
n;
t
h
e
r
e
f
o
r
e
,
di
f
f
e
r
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n
t
t
y
pe
s
o
f
f
u
s
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d
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m
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s
c
a
n
b
e
e
x
pe
c
t
e
d.
Al
t
h
o
ugh
t
h
e
‘
á
t
r
o
us
’
a
l
go
r
i
t
hm
a
ppe
a
r
s
t
o
b
e
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s
s
a
de
qua
t
e
t
h
a
n
t
h
e
M
a
ll
a
t
a
l
go
r
i
t
hm
w
h
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n
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x
t
r
a
c
t
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g
s
pa
t
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a
l
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t
a
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l
s
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n
t
h
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c
o
n
t
e
x
t
o
f
m
u
l
t
i
r
e
s
o
l
ut
i
o
n
a
n
a
ly
s
i
s
(
f
r
o
m
a
t
h
e
o
r
e
t
i
c
a
l
pe
r
s
p
e
c
t
i
v
e
)
,
t
h
i
s
a
l
go
r
i
t
hm
y
i
e
l
d
s
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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2502
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l
.
25
,
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o
.
1
,
J
a
n
ua
r
y
20
22
:
256
-
264
258
im
a
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s
w
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t
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i
g
nif
i
c
a
n
t
l
y
hi
g
h
e
r
g
l
o
ba
l
qua
li
t
y
[
38
]
.
F
or
t
h
e
s
i
x
m
e
t
h
o
ds
a
pp
l
i
e
d
i
n
t
hi
s
s
t
ud
y
,
a
n
R
G
B
(
t
r
ue
)
c
o
l
o
r
c
o
m
po
s
i
t
i
o
n
m
us
t
b
e
r
e
n
de
r
e
d
f
r
o
m
a
c
o
m
bi
na
t
i
o
n
o
f
t
h
e
M
UL
T
I
a
n
d
t
h
e
P
AN
s
u
b
-
i
m
a
ge
s
,
us
i
n
g
t
h
e
s
a
m
e
p
i
x
e
l
s
i
z
e
o
f
t
h
e
l
a
t
t
e
r
(
1
m
e
t
e
r
).
P
r
o
c
e
dur
e
f
o
r
i
m
p
l
e
m
e
n
t
i
n
g
2D
-
M
w
a
ve
l
e
t
tr
a
ns
f
o
r
m
,
(
A
m
o
d
i
f
i
c
a
t
i
o
n
t
o
t
h
e
wa
v
e
l
e
t
h
a
a
r
t
r
a
n
s
f
o
r
m
)
[
33
]
,
[
34]
:
-
S
t
e
p
1.
T
r
a
n
s
f
o
r
m
t
h
e
R
GB
i
m
a
ge
i
n
t
o
h
ue
,
s
a
t
ur
a
ti
o
n
,
v
a
l
ue
(
HSV
)
a
n
d
a
d
j
us
t
t
h
e
hi
s
t
o
gr
a
m
s
o
f
t
h
e
P
A
N
im
a
ge
a
n
d
t
h
e
V
c
o
m
po
n
e
n
t
,
y
i
e
l
d
i
ng
t
h
e
n
e
w
Va
p
c
o
m
po
n
e
n
t
.
-
S
t
e
p
2
.
A
pp
l
y
t
he
2D
-
M
w
a
v
e
l
e
t
t
r
a
n
s
f
o
r
m
t
o
t
h
e
V
c
o
m
po
n
e
n
t
(
s
e
c
o
n
d
de
c
o
m
po
s
i
t
i
o
n
l
e
v
e
l
)
,
yi
e
ld
i
n
g
t
h
e
c
or
r
e
s
po
n
d
i
n
g
a
ppr
o
xi
m
a
t
i
o
n
a
n
d
de
t
a
i
l
c
o
e
f
f
ic
i
e
n
t
s
;
t
h
e
A
1
v
a
ppr
o
xi
m
a
t
i
o
n
c
o
e
f
i
c
i
e
n
t
e
s
c
o
n
t
a
i
n
t
h
e
s
pe
c
t
r
a
l
i
n
f
o
r
m
a
t
i
o
n
o
f
t
h
e
i
m
a
g
e
;
m
e
a
n
w
hi
l
e
,
de
t
a
i
l
c
o
e
f
f
i
c
i
e
n
t
s
c
V1
v
,
c
H1
v
a
n
d
c
D1
v
s
t
o
r
e
t
h
e
s
pa
t
i
a
l
i
n
f
o
r
m
a
t
i
o
n
o
f
t
h
e
im
a
ge
.
De
c
o
m
po
s
e
t
h
e
A
1
v
a
s
e
c
o
n
d
t
i
m
e
,
yi
e
l
d
i
ng
t
h
e
A
2
v
a
ppr
o
xim
a
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
t
h
a
t
c
o
n
t
a
i
n
t
h
e
s
pe
c
t
r
a
l
i
nf
o
r
m
a
t
i
o
n
o
f
t
h
e
im
a
ge
;
m
e
a
n
w
hil
e
,
c
V2
v
,
c
H2
v
a
n
d
c
D2
v
a
l
o
n
g
w
i
t
h
c
V1
v
,
c
H1v
a
n
d
c
D1
v
c
o
r
r
e
s
po
n
d
to
t
h
e
de
ta
i
l
c
o
e
f
f
i
c
i
e
n
t
s
t
h
a
t
h
o
l
d
t
h
e
s
pa
t
i
a
l
i
nf
o
r
m
a
t
i
o
n
of
t
he
t
r
a
n
s
f
o
r
m
e
d
i
m
a
ge
.
-
S
t
e
p
3
.
A
p
p
l
y
t
h
e
2D
-
M
w
a
v
e
l
e
t
t
r
a
n
s
f
o
r
m
to
th
e
pa
n
c
h
r
o
m
a
t
i
c
im
a
ge
(
se
c
o
n
d
d
e
c
o
m
po
s
i
t
i
o
n
l
e
v
e
l
)
,
yi
e
l
d
i
ng
t
h
e
c
o
r
r
e
s
po
n
d
i
n
g
a
ppr
o
xim
a
t
i
o
n
a
n
d
d
e
t
a
i
l
c
o
e
f
f
i
c
i
e
n
t
s
;
t
h
e
A
1p
a
ppr
o
xi
m
a
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
c
o
n
t
a
i
n
t
h
e
s
pe
c
t
r
a
l
i
nf
o
r
m
a
t
i
o
n
o
f
t
h
e
i
m
a
ge
;
m
e
a
n
w
hil
e
,
de
t
a
i
l
c
o
e
f
f
i
c
i
e
n
t
s
c
V1p,
c
H1p
a
n
d
c
D1p
s
to
r
e
t
h
e
s
pa
t
i
a
l
i
n
f
o
r
m
a
t
i
o
n
.
De
c
o
m
po
s
e
A
1p
a
s
e
c
o
nd
t
i
m
e
t
o
o
b
t
a
i
n
t
h
e
A
2p
s
e
c
o
n
d
-
l
e
v
e
l
a
ppr
o
xi
mat
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
,
whi
c
h
c
o
n
t
a
i
n
t
h
e
s
p
e
c
t
r
a
l
i
n
f
o
r
m
a
t
i
o
n;
m
e
a
n
w
hil
e
,
c
V2p,
c
H2p
a
n
d
c
D2p
a
l
o
n
g
w
i
t
h
c
V1,
c
H1p
a
n
d
c
D1p
c
o
r
r
e
s
po
n
d
to
t
h
e
de
t
a
i
l
c
o
e
f
f
i
c
i
e
n
t
s
b
e
a
r
i
n
g
t
h
e
s
pa
t
i
a
l
i
n
f
o
r
m
a
t
i
o
n
o
f
t
h
e
t
r
a
n
s
f
o
r
m
e
d
im
a
ge
.
-
S
t
e
p
4
.
Ge
n
e
r
a
t
e
a
n
e
w
v
a
l
ue
c
o
m
po
n
e
n
t
(
NI
)
,
us
i
n
g
t
h
e
A2
v
c
o
e
f
f
i
c
i
e
n
t
s
t
h
a
t
s
t
or
e
t
h
e
i
nf
o
r
m
a
t
i
o
n
o
f
t
h
e
V
-
c
o
m
po
n
e
n
t
i
m
a
ge
t
o
ge
t
h
e
r
w
i
t
h
t
h
e
s
e
c
o
n
d
-
l
e
ve
l
d
e
t
a
i
l
c
o
e
f
f
i
c
i
e
n
t
s
o
f
t
h
e
pa
n
c
h
r
o
m
a
t
i
c
im
a
ge
(
c
V2p,
c
H2p
a
n
d
c
D2p
)
a
n
d
t
h
e
de
t
a
i
l
c
o
e
f
f
i
c
i
e
n
t
s
f
r
o
m
t
h
e
f
i
r
s
t
-
l
e
v
e
l
de
c
o
m
po
s
i
t
i
o
n
(
c
V1p,
c
H1p
a
n
d
c
D1p
)
.
-
S
t
e
p
5
.
A
pp
l
y
t
h
e
i
nve
r
s
e
2D
-
M
w
a
ve
l
e
t
t
r
a
n
s
f
o
r
m
to
o
b
t
a
i
n
t
h
e
n
e
w
i
n
t
e
n
s
i
t
y
c
o
m
po
n
e
n
t
(
NV
)
.
-
S
t
e
p
6
.
Gi
ve
n
t
h
e
n
e
w
NV
,
a
n
d
t
h
e
o
r
i
g
i
na
l
h
ue
a
nd
s
a
t
ur
a
t
i
o
n
c
o
m
po
n
e
n
t
s
,
ge
n
e
r
a
t
e
t
h
e
n
e
w
HS
-
NV
.
-
S
t
e
p
7
.
C
o
n
duc
t
t
h
e
i
nve
r
s
e
im
a
g
e
t
r
a
n
s
f
o
r
m
a
t
i
o
n
f
r
o
m
HS
-
NV
to
R
GB
.
T
h
us
,
t
h
e
n
e
w
m
u
l
t
i
s
pe
c
t
r
a
l
im
a
ge
i
s
o
b
t
a
i
ne
d,
whi
c
h
m
a
i
n
t
a
i
ns
t
h
e
s
p
e
c
t
r
a
l
r
e
s
o
l
ut
i
o
n
,
l
e
a
d
i
ng
to
a
ga
i
n
i
n
s
pa
t
i
a
l
r
e
s
o
l
ut
i
o
n
.
2
.
3.
Gr
am
-
s
c
h
m
id
t
T
h
e
Gr
a
m
-
S
c
hmi
dt
i
m
a
ge
-
f
us
i
o
n
m
e
t
h
o
d
i
s
b
a
s
e
d
o
n
a
ge
n
e
r
a
l
v
e
c
t
o
r
or
t
h
o
g
o
n
a
l
i
z
a
t
i
o
n
a
l
go
r
i
t
hm
.
T
h
e
a
l
go
r
i
t
hm
c
o
ns
i
s
t
s
i
n
t
a
k
i
n
g
n
o
n
-
o
r
t
h
o
g
o
n
a
l
ve
c
to
r
s
a
n
d
a
pp
l
y
r
o
t
a
t
i
o
n
t
o
m
a
ke
t
h
e
m
o
r
t
h
o
g
o
n
a
l
.
W
h
e
n
a
pp
l
i
e
d
t
o
i
m
a
ge
pr
o
c
e
s
s
i
ng,
e
a
c
h
b
a
n
d
(
t
h
e
pa
nc
h
r
o
m
a
t
i
c
,
t
h
e
r
e
d,
t
h
e
gr
e
e
n
,
t
h
e
bl
ue
a
n
d
t
h
e
inf
r
a
r
e
d)
c
o
r
r
e
s
po
n
ds
to
a
n
n
-
d
im
e
n
s
i
o
n
a
l
v
e
c
t
o
r
(
#
di
m
e
ns
io
n
s
=
#
pi
x
e
l
s
)
.
I
m
p
l
e
m
e
n
t
a
t
i
o
n
pr
o
c
e
dur
e
:
-
S
t
e
p
1.
S
i
m
u
l
a
t
e
t
h
e
pa
n
c
h
r
o
m
a
t
i
c
b
a
n
d
f
r
o
m
t
h
e
l
o
w
-
s
pa
t
i
a
l
-
r
e
s
o
l
ut
i
o
n
s
pe
c
t
r
a
l
ba
n
ds
.
-
S
t
e
p
2
.
A
pp
l
y
t
he
Gr
a
m
-
S
c
hm
i
dt
t
r
a
n
s
f
o
r
m
t
o
t
h
e
s
i
m
u
l
a
t
e
d
pa
n
c
h
r
o
m
a
t
i
c
b
a
n
d
a
n
d
a
l
s
o
to
t
h
e
s
pe
c
t
r
a
l
b
a
n
d
s
,
e
m
p
l
o
yi
ng
t
h
e
s
i
m
u
l
a
t
e
d
pa
n
c
h
r
o
m
a
t
i
c
b
a
nd
a
s
t
h
e
f
i
r
s
t
b
a
n
d
.
-
S
t
e
p
3
.
I
n
t
e
r
c
a
m
bi
a
r
l
a
a
l
t
a
r
e
s
o
l
uc
i
ó
n
e
s
pa
c
i
a
l
d
e
b
a
n
d
a
pa
n
c
r
o
m
á
t
i
c
a
c
o
n
l
a
pr
im
e
r
a
b
a
n
da
de
G
r
a
m
-
S
c
hmi
dt
.
-
S
t
e
p
4
.
A
pp
l
y
t
h
e
i
nve
r
s
e
Gr
a
m
-
S
c
hmi
dt
t
r
a
n
s
f
o
r
m
to
c
o
n
s
t
r
uc
t
t
h
e
hi
g
h
-
r
e
s
o
l
ut
i
o
n
s
pe
c
t
r
a
l
b
a
n
d
s
.
2
.
4.
Hi
gh
-
f
r
e
q
u
e
n
c
y
m
od
u
l
at
ion
T
hi
s
m
e
t
h
o
d
i
s
a
va
r
i
a
t
i
o
n
o
f
t
h
e
s
o
-
c
a
l
l
e
d
s
pa
t
i
a
l
-
do
m
a
i
n
f
u
s
i
o
n
m
e
t
h
o
ds
[
39]
,
whi
c
h
f
o
c
us
o
n
t
r
a
n
s
f
e
r
r
i
n
g
t
h
e
hi
g
h
f
r
e
que
nc
i
e
s
o
f
a
hi
g
h
-
r
e
s
o
l
ut
i
o
n
i
m
a
ge
o
n
to
a
l
o
w
-
r
e
s
o
l
ut
i
o
n
im
a
ge
.
T
h
e
hi
g
h
-
f
r
e
que
nc
y
r
e
pr
e
s
e
n
t
a
t
i
o
n
o
f
a
n
i
m
a
ge
c
o
n
t
a
i
ns
t
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[
1]
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.2007.904923.
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461,
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358
-
367, 2014, do
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/9
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-
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_37.
[
4]
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.
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,
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.i
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.2016.03.003
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726,
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278.
[
10]
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.
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100642, 202
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.
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.2021.100642.
[
11]
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.
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o
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gl
e
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r
th
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ngi
n
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f
or
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n
nua
l
e
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ma
te
s
of
la
nd
s
ur
f
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c
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ph
e
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o
l
o
g
y
in
a
he
t
e
r
o
g
e
n
o
us
la
nds
c
a
pe
,
”
I
nt
e
r
nat
io
nal
J
our
nal
of
A
ppl
ie
d
E
ar
th
O
b
s
e
r
v
at
io
n
and
G
e
oi
nf
o
r
m
at
io
n
,
vo
l.
99,
p.
102323, 2021, d
o
i:
10.1016/j
.j
a
g.20
21.102323.
[
14]
S
.
W
u
a
nd
H
.
C
h
e
n,
“
S
ma
r
t
c
i
t
y
o
r
i
e
nt
e
d
r
e
m
o
t
e
s
e
ns
in
g
i
ma
ge
f
us
i
o
n
m
e
th
o
ds
ba
s
e
d
o
n
c
o
n
vo
lu
ti
o
n
s
a
mpl
in
g
a
nd
s
pa
ti
a
l
tr
a
ns
f
o
r
ma
ti
o
n
,
”
C
om
put
e
r
C
om
m
uni
c
at
io
ns
,
v
o
l.
157,
pp.
444
-
450, 2020, do
i:
10.1016/j
.
c
o
m
c
o
m.2020.04.010.
[
15]
D
.
L
i
,
Z
.
S
o
ng,
C
.
Q
ua
n,
X
.
X
u,
a
nd
C
.
L
iu
,
“
R
e
c
e
nt
a
d
v
a
nc
e
s
in
im
a
ge
f
us
i
o
n
t
e
c
hn
o
l
o
g
y
in
a
gr
ic
ul
tu
r
e
,
”
C
om
put
e
r
s
and
E
le
c
tr
oni
c
s
i
n A
gr
ic
ul
tu
r
e
,
v
o
l.
191,
p.
106491, 2021, d
o
i:
10.1
016/
j.
c
o
mpa
g.2021.106491.
[
16]
J
.
K
o
ng
e
t
al
.,
“
E
v
a
lu
a
ti
o
n
of
f
o
u
r
im
a
g
e
f
us
i
o
n
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V
I
p
r
o
duc
ts
a
ga
in
s
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in
-
s
it
u
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pe
c
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-
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ur
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nt
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ov
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o
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r
ic
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dd
y
l
a
nds
c
a
pe
,
”
A
gr
ic
ul
tu
r
al
and F
or
e
s
t
M
e
te
or
ol
ogy
,
vo
l.
2
97,
p.
108255, 2021, do
i:
10.1016/j
.a
g
r
f
o
r
m
e
t.
2020.108255.
[
17]
Z
.
C
a
o
,
S
.
C
h
e
n,
F
.
G
a
o
,
a
nd
X
.
L
i,
“
I
mpr
ov
in
g
ph
e
n
o
l
o
gi
c
a
l
mo
ni
t
or
in
g
of
w
in
t
e
r
w
h
e
a
t
b
y
c
o
ns
id
e
r
in
g
s
e
ns
or
s
pe
c
tr
a
l
r
e
s
p
o
ns
e
in
s
pa
ti
o
t
e
mp
o
r
a
l
im
a
ge
f
us
i
o
n
,
”
P
hy
s
ic
s
and
C
he
m
is
tr
y
of
th
e
E
ar
th
,
P
ar
ts
A
/B
/C
,
vo
l.
116,
p.
102859,
2020,
do
i:
10.1016/j
.pc
e
.2020.102859.
[
18]
Y
.
L
i,
J
.
Z
h
a
o
,
Z
.
L
v,
a
nd
J
.
L
i,
“
M
e
d
ic
a
l
im
a
ge
f
us
i
o
n
m
e
th
od
b
y
d
e
e
p
l
e
a
r
ni
ng
,
”
I
nt
e
r
nat
io
nal
J
our
nal
of
C
ogni
ti
v
e
C
om
put
in
g
in
E
ngi
ne
e
r
in
g
,
vo
l.
2,
pp.
21
-
29, 2021, d
o
i
:
10.1016/j
.i
j
c
c
e
.202
0.12.004.
[
19]
H
.
X
u
a
nd
J
.
M
a
,
“
E
M
F
us
i
o
n:
A
n
uns
up
e
r
v
is
e
d
e
nha
n
c
e
d
me
di
c
a
l
im
a
g
e
f
us
io
n
ne
tw
or
k
,
”
I
nf
or
m
at
io
n
F
us
io
n
,
vol
.
76,
pp.
177
-
186, 2021, do
i
:
10.1016/j
.i
n
f
f
us
.2021.06.001.
[
20]
X
.
L
i,
F
.
Z
h
o
u,
a
nd
H
.
T
a
n,
“
J
o
in
t
im
a
g
e
f
us
io
n
a
nd
de
n
o
is
in
g
vi
a
th
r
e
e
-
la
y
e
r
d
e
c
o
mp
o
s
it
i
o
n
a
nd
s
pa
r
s
e
r
e
p
r
e
s
e
nt
a
ti
o
n
,
”
K
now
le
dge
-
B
as
e
d Sy
s
te
m
s
,
v
o
l.
224,
p.
107087, 2021, d
o
i:
10.1
016/
j.
kno
s
y
s
.2021.107087.
[
21]
G
.
L
i,
Y
.
L
in
,
a
nd
X
.
Q
u,
“
A
n
in
f
r
a
r
e
d
a
nd
v
is
ib
le
im
a
ge
f
us
io
n
me
th
o
d
ba
s
e
d
o
n
mul
ti
-
s
c
a
l
e
t
r
a
ns
f
or
ma
ti
o
n
a
nd
n
o
r
m
o
pt
im
i
z
a
ti
o
n
,
”
I
nf
or
m
at
io
n F
us
io
n
,
vo
l.
71,
pp.
109
-
129, 2021,
do
i:
10.1016/j
.
in
f
f
us
.2021.02.008.
[
22]
M
.
M
is
it
i,
Y
.
M
is
it
i,
G
.
O
ppe
nhe
im
,
a
nd
J
.
-
M
.
P
o
ggi
,
W
av
e
le
ts
to
ol
box
F
or
us
e
w
it
h
M
at
la
b,
T
h
e
M
a
ht
w
o
r
ks
I
n
c
,
N
a
ti
c
k,
M
A
01760
-
2098, Ve
r
s
i
o
n 4.4.1., 2009.
[
23]
Y
. N
ie
v
e
r
ge
lt
,
W
av
e
le
ts
m
ade
e
as
y
,
E
d B
ir
khä
us
e
r
, N
e
w
Y
o
r
k,
2013, do
i:
10.1007/978
-
1
-
4614
-
6006
-
0.
[
24]
C
. B
ur
r
us
,
W
av
e
le
ts
and W
av
e
le
t
T
r
ans
f
or
m
s
, S
e
p
.
24, 2015, htt
p:
//
c
n
x
.
or
g/
c
o
n
te
nt
/
c
o
l
11454/1.6
/
[
25]
G
.
S
id
da
li
ng
e
s
h,
A
.
M
a
ll
ik
a
r
ju
n,
H
.
S
a
nj
e
e
v
kuma
r
,
a
nd
S
.
K
ot
r
e
s
h,
“
F
e
a
tu
r
e
-
L
e
ve
l
I
ma
ge
F
us
i
o
n
U
s
in
g
D
W
T
,
S
W
T
,
a
nd
D
T
-
C
W
T
,
”
E
m
e
r
gi
ng
R
e
s
e
ar
c
h i
n E
le
c
tr
oni
c
s
, C
om
put
e
r
Sc
ie
nc
e
, and T
e
c
hnol
ogy
, L
e
c
tu
r
e
N
ot
e
s
i
n E
le
c
tr
ic
al
E
ngi
ne
e
r
in
g
,
v
ol
.
248,
pp.
183
-
194, 2014, do
i
:
10.1007/978
-
81
-
322
-
1157
-
0_20.
[
26]
N
.
J
ha
,
A
.
K
.
S
a
x
e
na
,
A
.
S
hr
i
v
a
s
ta
v
a
,
a
nd
M
.
M
a
no
r
ia
,
“
A
r
e
v
i
e
w
o
n
v
a
r
i
o
us
im
a
ge
f
us
i
o
n
a
lg
or
it
hms
,
”
2017
I
nt
e
r
nat
io
nal
C
onf
e
r
e
nc
e
on
R
e
c
e
nt
I
nnov
at
io
ns
in
Si
gnal
P
r
oc
e
s
s
in
g
and
E
m
be
dde
d
Sy
s
te
m
s
(
R
I
SE
)
,
O
c
t.
2017,
pp.
27
-
29
,
do
i:
10.1109/
r
is
e
.2017.8378146
.
[
27]
C
.
P
e
r
i
y
a
s
a
m
y
,
“
S
a
t
e
ll
it
e
I
ma
ge
E
nha
nc
e
m
e
nt
U
s
in
g
D
ua
l
T
r
e
e
C
ompl
e
x
W
a
ve
l
e
t
T
r
a
ns
f
o
r
m
,
”
B
ul
le
ti
n
of
E
le
c
tr
ic
al
E
ngi
ne
e
r
in
g
and I
nf
or
m
at
ic
s
,
v
ol
.
6,
n
o
.
49,
pp.
334
-
336, 2017, d
o
i:
10.1159
1/
e
e
i.
v
6i
4.861.
[
28]
A
.
S
ha
r
ma
a
nd
T
.
G
ul
a
ti
,
“
C
ha
nge
D
e
t
e
c
ti
o
n
f
r
o
m
R
e
m
o
t
e
l
y
S
e
ns
e
d
I
ma
ge
s
B
a
s
e
d
o
n
S
ta
ti
o
na
r
y
W
a
ve
l
e
t
T
r
a
ns
f
o
r
m
,
”
I
nt
e
r
nat
io
nal
J
our
nal
o
f
E
le
c
t
r
ic
al
and
C
om
put
e
r
E
ngi
ne
e
r
in
g
,
v
o
l.
7,
no
.
6,
pp.
3395
-
3401,
2017,
do
i:
10.11591/i
je
c
e
.
v
7i
6.pp3395
-
3401.
[
29]
V
.
R
a
dhi
ka
,
K
.
V
e
e
r
a
s
w
a
m
y
,
a
nd
S
.
S
.
K
uma
r
,
“
D
ig
it
a
l
I
ma
g
e
F
us
io
n
U
s
in
g
H
V
S
in
B
l
oc
k
B
a
s
e
d
T
r
a
ns
f
or
ms
,
”
J
Si
gn
P
r
oc
e
s
s
Sy
s
t
,
v
ol
.
90,
pp.
947
-
957, 201
8, d
o
i:
10.1007/s
11265
-
017
-
125
2
-
8.
[
30]
Y
.
L
iu
,
L
.
W
a
ng,
J
.
C
he
ng,
C
.
L
i,
a
nd
X
.
C
h
e
n,
“
M
ul
ti
-
f
oc
us
i
ma
ge
f
us
i
o
n:
A
S
ur
ve
y
of
th
e
s
ta
te
of
th
e
a
r
t
,
”
I
nf
or
m
at
io
n
F
us
io
n
,
vo
l.
64,
pp.
71
-
91, 2020, d
oi
:
10.1016/j
.i
n
f
f
us
.2020.06.013.
[
31]
M
.
J
in
da
l,
E
.
B
a
ja
l,
A
.
C
ha
kr
a
bo
r
t
y
,
P
.
S
in
gh,
M
.
D
iwa
ka
r
,
a
nd
M
.
K
uma
r
,
“
A
no
ve
l
mul
ti
-
f
oc
us
im
a
ge
f
us
io
n
pa
r
a
di
gm
:
A
h
y
br
id
a
pp
r
o
a
c
h
,
”
M
at
e
r
ia
ls
T
oday
:
P
r
oc
e
e
di
ngs
,
vo
l.
37, P
a
r
t
2,
pp.
2952
-
2958, 2021, do
i
:
10.1016/j
.ma
tp
r
.2020.08.704.
[
3
2
]
J
.
N
u
ñ
e
z
,
X
.
O
t
a
z
u
,
O
.
F
o
r
s
,
A
.
P
r
a
d
e
s
,
V
.
P
a
l
a
,
a
n
d
R
.
A
r
b
i
o
l
,
“
M
u
l
t
i
r
e
s
o
l
u
ti
o
n
-
B
a
s
e
d
I
m
a
ge
f
u
s
i
o
n
w
h
i
t
A
d
d
i
t
iv
e
W
a
v
e
le
t
D
e
s
c
o
m
po
s
i
t
io
n
,
”
I
E
E
E
T
r
a
n
s
a
c
t
i
o
n
s
o
n
G
e
o
s
c
i
e
n
c
e
a
n
d
R
e
m
o
t
e
S
e
n
s
i
n
g
,
v
ol
.
37,
no
. 3, pp
.
1204
-
1211, 1999, d
o
i:
10.1109/
36.76327
4.
[
33]
J
.
M
e
di
na
,
C
.
P
in
il
la
,
a
nd
L
.
J
oy
a
n
e
s
,
“
T
w
o
-
D
im
e
ns
io
na
l
F
a
s
t
H
a
a
r
W
a
ve
l
e
t
T
r
a
ns
f
o
r
m
f
or
S
a
te
ll
it
e
-
I
ma
g
e
F
us
i
o
n
,
”
J
our
na
l
of
A
ppl
ie
d R
e
m
ot
e
Se
ns
in
g
,
vo
l.
7,
n
o
.
1,
p.
073698, 2013, d
o
i:
10.
1117/1.J
R
S
.7.073698.
[
34]
E
.
U
pe
gui
a
nd
J
.
M
e
di
na
,
A
nál
is
is
d
e
I
m
áge
ne
s
u
s
ando
la
s
tr
as
f
or
m
ada
s
F
our
ie
r
y
W
av
e
le
t
,
B
o
g
o
tá
:
E
di
t
or
ia
l
U
ni
ove
r
s
i
da
d
D
is
tr
it
a
l
F
r
a
nc
is
c
o
J
o
s
é
de
C
a
ld
a
s
, 2019, I
S
B
N
978
-
787
-
064
-
0.
[
35]
C
.
G
o
n
z
a
l
o
a
nd
M
.
L
il
l
o
-
S
a
a
ve
dr
a
,
“
A
di
r
e
c
t
e
d
s
e
a
r
c
h
a
lg
or
it
h
m
f
o
r
s
e
tt
in
g
th
e
s
pe
c
t
r
a
l
–
s
pa
ti
a
l
qua
li
t
y
tr
a
de
-
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,
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C
anadian J
our
nal
of
R
e
m
ot
e
S
e
ns
in
g
,
v
ol
.
34
, n
o
.
4,
pp.
367
-
375, 2008, d
o
i:
10.5589/m
08
-
04
1.
[
36]
R
. C
. G
o
n
z
á
l
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z
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nd
R
. E
. W
oo
ds
,
D
ig
it
al
I
m
age
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r
oc
e
s
s
in
g
, 4t
h. E
di
ti
o
n, P
e
a
r
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n, 2018,
I
S
B
N
:
9780133356779.
[
37]
J
.
M
e
di
na
,
I
.
C
a
r
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il
lo
,
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nd
E
.
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p
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mpl
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I
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,
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o
.
E
41, pp. 396
-
409
, 2021
.
[
38]
C
.
G
o
n
z
a
l
o
-
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a
r
tí
n
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nd
M
.
L
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us
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in
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m
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r
ans
ac
ti
ons
,
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o
l.
5,
n
o
.
1,
pp
.
32
-
37,
2007,
do
i:
10.1109/
T
-
L
A
.2007.4444530.
[
39]
R
. A
. S
c
h
o
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e
r
dt
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m
o
t
e
S
e
ns
in
g. M
o
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a
nd M
e
th
o
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oc
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s
s
in
g, 3r
d e
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ls
e
i
ve
r
,
2013
.
[
40]
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e
x
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go
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G
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l,
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R
D
A
S I
m
agi
ne
2018
, O
nl
in
e
D
oc
um
e
nt
a
ti
o
n, 2018.
[
41]
C
.
P
o
hl
a
nd
J
.
L
.
V
a
n
G
e
nd
e
r
e
n,
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nt
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r
nat
io
nal
J
our
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m
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and Data F
us
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,
vo
l.
6,
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o
.
1,
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3
-
21,
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i:
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.1080/19479832.201
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[
42]
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.
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pos
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.1989.577945.
[
43]
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A
m
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r
ans
ac
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ons
,
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o
l.
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.
12,
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.
2130
-
21
37,
2020, do
i:
10.1109/
T
L
A
.2020.9400441.
[
44]
S
. R
. M
ur
r
a
y
a
nd J
. F
.
L
a
r
r
y
,
E
s
ta
dí
s
ti
c
a
, C
ua
r
ta
e
di
c
ió
n, M
c
G
r
a
w
H
il
l,
2009.
[
45]
L
.
W
a
ld
,
D
at
a
F
us
io
n,
D
e
f
in
it
io
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r
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te
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tu
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us
io
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m
age
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e
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Spat
ia
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e
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e
s
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l
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o
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s
M
in
e
s
, P
a
r
is
, 2002.
[
46]
L
.
W
a
ld
,
“
Q
ua
li
t
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gh
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e
s
o
lu
ti
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ngs
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us
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nt
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r
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.
[
47]
M
.
L
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.
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o
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.
26,
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1263
-
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i:
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12331330239.
[
48]
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