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Mapping without the sun
Zhang, Jixian

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.
/=0 7 =0
M-1 N-1
i=0 7=0 /=0 7=0
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
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