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Title
Mapping without the sun
Author
Zhang, Jixian

26
Pixel-
based
No Grouping
Choose max
Window-
based
Single-scale
GrouDins
Weighted
Average
Region-
based
Multi-scale
Grouping
AMO
Results
Schemes
Activity Level Grouping method Combining method
Figure 2. The flowchart of the image fusion procedure
Consistency
Verification
Table 1 Some used abbreviations in the paper
Abbreviation
Description
AMO
Adaptive multi-objective optimization
CBA
Coefficient-based activity level
CM
Choose-max coefficient combining
DWT
Discrete wavelet transform
LPT
Laplacian pyramid transform
MG
Multiscale grouping
MORPH
Morphological pyramid
NG
No grouping
RBV
Region-based consistency verification
SiDWT
the shift invariant DWT
WA
Weighted average coefficient combining
WBA
Window-based activity measurement
ADD
LPT MORPH
(a) WA-WBA+NG+CM+NV
DWT
MORPH DWT SiDWT
(b) WA-WBA+NG+AMO+RBV
SiDWT
Figure 3. Results of two fusion methods
Table 2. Performance of Fig.3 (b) method when Using Different decomposition levels
Combination
MSD(Levell)
SD
EN
CE
MI
UI
WA-WBA+
NG+
AMO+
RBV
LPT
61.7211
7.3811
2.1661
3.2951
0.7036
Morph
61.5777
6.7915
2.6465
5.7916
0.7212
DWT
61.1049
7.5614
1.9310
2.7441
0.7090
SiDWT
61.5212
7.1839
2.4275
5.1667
0.7231
Trough the
Morph, DWT,
can find use tl
combing coeffi
better quality tl
1), we find w
region easily i
speckle noise,
space resolutioi
in the image 1
water region).",
origins (e.g.
resolution of t
needed. Throu
distinguish wa
method (b) tha
multi-objective
combing to sea
3(b). Therefore
search the ada
can save up th
huge different
simple combii
performances.
Meanwhile,
images from d
table 2, the MI
than do the 01
MORPH the
measure indica
For poor fusio
MI assigns the
the DWT fusic
lower than Si
observers. CE
remarkable in 1
As one can <
SD, to extract
apparent corre
evaluations. El
in the fused im
values for the
sensitivity of
fluctuations in
discriminate b<