231 
Map Info: 
r (File) 
Projection Info: 
Upper Left X: 511000.0 
Upper Left Y: 3411000.0 
Lower Right X: 520990.0 
Lower Right Y: 3401010.0 
Pixel SizeX: 10.0 
Pixel Size Y: 10.0 
Unit: meters 
Geo. Model: Map Info 
Projection: Transverse Mercator 
Spheroid: Krasovsky 
Datum: Krasovsky 
Figure 3. Imageinformation 
Figure 4. Image aggregation of differentspatial resolution 
3.2 Fused Images Obtained by Different Fusion Method 
Image fusing methods are mainly Color Model Method (Hue 
Intensity Saturation, HIS), Principal Component Analysis 
Method(PCA), Multiplicative Method, Brovey Method and so 
on. The effect to spatial resolution is different from different 
fusing methods. 
Figure 1 and Figure 2 are fused by the methods mentioned 
above. And then, the fused images are obtained, which are 
Figure 5, Figure 6, Figure 7 and Figure 8. 
Figure 5. HIS 
Figure 6. PC A 
3.3 Criterions of Determining Fused Image Quantitatively 
3.3.1 Correlation Coefficient: Correlation Coefficient 
describes similarity degree of two images[Sun J.B., 2003]. 
Function (1) is about it. 
M-lN-l 
/=0 7 =0 
M-lN-l 
M-1 N-1 
1/2 
[IZCAyi-AfllCMU)-/*)] 
i=0 7=0 /=0 7=0 
(i) 
where r = correlation coefficient 
M = total number of the image row 
N = total number of the image column 
(*’./) = number of the row and column 
f A 0’ 7 ) = g ra y va i ue 0 f the different resolution 
image 
Ib (*> J') = g ra y value of the fused image 
f f 
J A J B - average gray value of images 
Correlation coefficients between different resolution images 
and fused image can be computed by Function (1). The bigger 
the correlation coefficient is, the closer the resolution of the 
fused image and the resolution of the high resolution is. 
Figure 7. Multiplicative Figure 8. Brovey