The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
1229 
D _ ^Li v n 
U MBTi ~ n D H 
2Л 
/■=1 
images, А/, is the mean radiance value of original image and 
(3) RMSE(Bj) is defined as: 
RMSB,B i ) = •¡(M i - FU§) 2 (6) 
Where n is total number of LSR images. 
3. EXPERIMENTT RESULTS AND ANALYSIS 
In this section, we consider two different data sets acquired by 
Quickbird and IKONOS satellite sensors, respectively. The 
purpose of selecting two types of sensors is to demonstrate that 
selected fusion methods work for both very high spatial 
resolution image. In order to assess the effectiveness of the 
proposed method, МВТ is compared with the fusion methods 
which can also fuse either individual band LSR images, such as 
SFIM and DWT. Three fusion methods are all achieved on the 
ERDAS IMAGE 8.7 platform. SFIM and МВТ are achieved 
under spatial modeler. DWT based on ERDAS IMAGE 8.7 
platform is a modification of the work of King (King et al,2001) 
with extensive input from Lemeshewsky (Lemeshewsky, 1999a; 
Lemeshewsky,2002b). The spectral quality and spatial quality 
of the fused images will be evaluated by the following indexes. 
3.1 Information Preservation Evaluation 
3.1.1 Spectral Quality of the Fusion Methods: The fused 
images gain spectral information from LSR images, so, the 
spectral quality of the fusion methods will be evaluated by the 
comparing their spectral quality with that of the original LSR 
images. The comparing is performed by the following indexes. 
Spectrum Difference (SD) between original LSR images and 
the fused images. 
SD = 
1 ^ "LSR jk -FUS jk 
MNjih LSR jk 
(4) 
Where FUSi represents the radiance of the /th band fused image. 
The lower value of SD and spectral ERG AS indexes, the higher 
the spectral quality of the merged images. The values of SD and 
ERGAS indexes are zero in ideal condition, and fusion method 
has optimal spectral information preservation when the values 
of SD and ERGAS indexes are closer to zero. 
3.1.2 Spatial Quality of the Fusion Methods: The fused 
images gain spatial information from HSR image, and the 
spatial quality of the fusion methods will be evaluated by the 
relationship between the fused images with HSR image using 
the indicators of Correlation Coefficient (CC) and spatial 
ERGAS (Lillo-Saavedra et al,2005). CC is got by: 
M N 
> уj )- f) №,, уj)-o) 
cc= 
'■=1 J 
(7) 
M N 
YY.(m,y,)-n 2 (o(x„y,)-öf 
M j=\ 
Where F(x, y) and 0(x, y) are the pixel grey values of fused and 
HSR images respectively, f is the mean value of fused image, 
and O is the mean value of HSR image. 
Spatial ERGAS is similar with spectral ERGAS. A spatial RMSE 
index is included in spatial ERGAS definition, and spatial 
RMSE is got by: 
-M HSR f +(SD n -SD HSR f (8) 
Where MN is the total number of pixels of original and fused 
images, FUS jk is the radiance value of pixel j in the Afii band of 
the fused image, and LSR jk is the radiance value of pixel j in the 
Mi band of original LSR image. 
The index SD can only evaluate the spectral quality of 
individual band. The spectral ERGAS (Wald,2000) index has 
been selected to estimate the global spectral quality of the 
fusion methods, and spectral ERGAS is defined as: 
Where M Fi and M HS r are the means of fused image and HSR 
image respectively, SD Fi and SD hsr are, respectively, standard 
deviation of fused image and HSR image. 
Higher CC or lower spatial ERGAS values imply that fusion 
method has higher spatial quality. In ideal condition, the values 
of CC and spatial ERGAS are 1 and zero, respectively. Fusion 
method has optimal spatial information preservation with HSR 
image when the values of CC are high and the values of spatial 
ERGAS are lower. 
ERGAS = 100 
h 1 
y J-ZC 
I V n M 
RMSE{B i Y 
M 2 
) 
(5) 
Where h is the spatial resolution of HSR image, / is the spatial 
resolution of LSR image, n is the total number of the fused 
3.2 Results on Quickbird Images 
A scene of Quickbird images (1600x1600 pixels for HSR image) 
taken on 21 Nov.2002 were selected as one test data in this 
paper. The test region of Quickbird covers urban areas of 
Sundarbans in India. Small areas (308x152 pixels for LRS 
image) of original HSR and LSR images are shown in Fig. 3.