In: Wagner W., Székely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B
i
387
Zhang, Y., and Wang, R., 2004. Multi-resolution and multi-
spectral image fusion for urban object extraction. In: XXth
ISPRS Congress, Commission III, Istanbul, Turkey, pp. 960-
966.
Zhou, J., Civco, D., and Silander, J. 1998. A wavelet transform
method to merge Landsat TM and SPOT panchromatic data,
International Journal of Remote Sensing. 19(4), pp. 743-757.
Spectral consistency
Spatial consistency
Fusion
SSIM,
SSIM
ERGAS,
SAM,
SSIM
SSIM
ERGAS
CORR
CORR
HPCC,
HPCC
PC
PC ZNCC
Method
ideal=l
(mean)
ideal=0
ideal=0
PAN,
PAN
PAN,
PAN,
PAN
ideal=l
(mean)
ZNCC,
(mean)
ideal=l
(mean)
ideal=0
ideal=l
(mean)
ideal=l
1
ATWT
0.9527
0.8883
1.2804
1.0164
0.6339
0.7488
3.7802
0.7939
0.8412
0.7604
0.77
0.7675
0.7821
0.8940
0.7474
0.8467
0.7679
0.7789
0.8604
0.8018
0.8625
0.7685
0.7738
0.8459
0.8122
0.8615
0.7991
0.8084
2
IHS
0.1737
0.2182
13.0793
5.2042
0.6184
0.6314
11.1713
0.9890
0.9898
0.9864
0.99
0.9566
0.9589
0.2042
0.5890
0.9930
0.9882
0.9630
0.2767
0.6870
0.9876
0.9860
0.9571
3
PCA
0.8036
0.7047
2.4393
1.5413
0.8379
0.9307
3.0968
0.9276
0.9433
0.9914
0.9944
0.9430
0.9468
0.6736
0.9623
0.9762
0.9971
0.9630
0.6311
0.9879
0.9825
0.9979
0.9651
0.7103
0.9346
0.8870
0.9912
0.9162
4
GIF-1
0.7462
0.6405
2.9900
1.1484
0.9040
0.9457
3.0098
0.9349
0.9545
0.9929
0.99
0.9444
0.9447
0.6079
0.9705
0.9665
0.9941
0.9507
0.5693
0.9516
0.9725
0.9941
0.9499
0.6386
0.9567
0.9443
0.9918
0.9341
5
GIF-2
0.7057
0.7076
2.3506
0.7142
0.8947
0.9359
3.1691
0.8960
0.9257
0.9846
0.9885
0.9157
0.9216
(90%)
0.6666
0.9628
0.9571
0.9928
0.9494
0.7293
0.9551
0.9520
0.9912
0.9233
0.7288
0.9308
0.8978
0.9854
0.8980
Table 1. Spectral and spatial consistency assessment of the pan-sharpened image dataset (first assessment setup)
Spectral consistency
Spatial consistency
Fusion
SSIM,
SSIM
ERGAS,
SAM,
SSIM
SSIM
ERGAS
CORR
CORR
HPCC,
HPCC
PC
PC ZNCC
Method
ideal=l
(mean)
ideal=0
ideal=0
PAN,
PAN
PAN,
PAN,
PAN
ideal=l
(mean)
ZNCC,
(mean)
ideal=l
(mean)
ideal=0
ideal=T
(mean)
ideal=l
1
GIF-2
0.7057
0.7076
2.3506
0.7142
0.8947
0.9359
3.1691
0.8960
0.9257
0.9846
0.9885
0.9157
0.9216
(90%)
0.6666
0.9628
0.9571
0.9928
0.9494
0.7293
0.9551
0.9520
0.9912
0.9233
0.7288
0.9308
0.8978
0.9854
0.8980
2
GIF-2
0.7333
0.7366
2.0316
0.7002
0.8591
0.9091
3.2778
0.8827
0.9136
0.9816
0.9837
0.8116
0.8131
(75%)
0.7011
0.9335
0.9389
0.9874
0.8654
0.7594
0.9300
0.9350
0.9852
0.8097
0.7529
0.9139
0.8980
0.9808
0.7658
3
GIF-2
0.8205
0.8277
1.4732
0.6344
0.7706
0.8207
3.5938
0.8521
0.8758
0.9412
0.9421
0.7024
0.6618
(50%)
0.8053
0.8412
0.8952
0.9464
0.6968
0.8462
0.8408
0.8923
0.9431
0.6368
0.8391
0.8302
0.8638
0.9379
0.6114
Table 2. Spectral and spatial consistency assessment of GIF-2 pan-sharpened image dataset (second assessment setup)
Added high frequency, % (GIF-2 method)
Figure 2. Dependency of spectral consistency measures on
added high frequency in GIF-2 method (Table 2)
Figure 3. Dependency of spatial consistency measures on
added high frequency in GIF-2 method (Table 2)