Full text: Proceedings; XXI International Congress for Photogrammetry and Remote Sensing (Part B7-3)

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
The correlation coefficient reflects the redundancy degree of 
images. According the table 1,we know the original image 
contains a plenty of redundant information and the correlation 
coefficient of fused image based on three-band biorthogonal 
wavelet is less than that of original image and other fused image 
except of fused image based on PCA, which indicates that this 
method has less redundant information . 
The mean gradient reflects the contrast between the details 
variation of pattern on the image and the clarity of the image. 
Of all images including original TM image ,the fused image 
based on three-band biorthogonal wavelet transform has the 
most mean gradient. 
According to previous statistics and analysis, we can draw a 
conclusion that the fusion method based on three-band 
biorthogonal wavelet is efficient for merging low resolution 
multi-spectral TM image and high resolution Spot panchromatic 
image.lt has many advantages in comparison with other 
methods when the ratio of spatial resolution of original image is 
not two.Certainly other fusion methods have advantage in some 
ways. 
Method 
MG 
SD 
CC 
CE 
34.07 
46.72 
0.296 
35.73 
52.38 
0.389 
PCA 
26.95 
53.30 
-0.25 
7.668 
31.77 
53.14 
0.647 
32.12 
46.45 
0.774 
IHS 
27.52 
52.83 
0.617 
7.661 
33.39 
52.81 
0.776 
Brovey 
34.31 
27.68 
46.07 
0.661 
7.683 
52.99 
0.463 
3-band 
39.82 
56.33 
0.578 
Biorthogonal 
44.63 
52.93 
0.523 
7.786 
Wavelet 
33.95 
58.83 
0.00718 
Original 
35.89 
52.89 
0.587 
7.70 
Image 
36.81 
49.40 
0.533 
(TM) 
29.99 
55.14 
0.03 
Table 1 the comparison of fused image of different methods 
5. CONCLUSIONS 
In this paper, a new fusion method based on three-band 
biorthogonal wavelet was presented to merge the multi-spectral 
TM and high resolution Spot panchromatic image. Several 
parameter including mean gradient, standard deviation, 
correlation coefficient and combination entropy were adopted 
to appraise the fused products. At last the result of experiment 
proves that the fusion method based on three-band biorthogonal 
wavelet is more efficient to fuse the TM 30m-resolution image 
and lOm-resolution Spot panchomatic image than other fusion 
methods. The reason is that biorthogonal wavelet is symmetric 
and three-band wavelet can produce the low frequency image 
which has the same resolution with low-resolution image.Thus 
the spectral information can be reseaved to the greatest extent 
and the distoration of spectral characters can be resolved. 
Further we can draw a conclusion that n-band biorthogonal 
wavelet has some advantages when the ratio of spatial 
resolution is n. So the multi-band biorthogonal wavelet can play 
a impotant role in image fusion. 
6. REFERENCES 
Aiazzi, B., L. Alparone, S. Baroni, A. Garzelli,2002. Context- 
Driven Fusion of Spatial and Spectral Resolution Images Based 
on Oversampled Multiresolution Analysis, IEEE Transaction 
on Geoscience and Remote Sensing, 40(10), pp2300-2312 
Chavez P. S. and Kwarteng A. Y., 1989.Extracting spectral 
contrast in Landsat Thematic Mapper image data using 
selective principle component analysis, Photogramm. Eng. 
Remote Sens., 55(3), pp.339-348 
Daubechics, I.,1992. Ten Lectures on wavelets, CBMSNSF 
Series in Applied Mathematics, 61, SIAM, 
Philadelphi,Pennsylvania, pp. 125-146 
Edwards. K. and Davis ,P. A.,1994.The use of Intensity-Hue- 
Saturation transformation for producing color shaded-relief 
images, Photogramm. Eng.Remote Sens, 60(11), pp. 1369-1374 
Gillespie .A. R., Kahle .A. B and Walker .R. E.,1987 .Color 
enhancement of highly correlated images—II. Channel ratio 
and ‘chromaticity’ transformation techniques. Remote Sens. 
Environ., 22, pp. 343-365 
Mallat. S, 1989. Theory for multi-resolution signal: The wavelet 
representation, IEEE Trans. Pattern Anal. Mach. Intell., vol. 11, 
no. 7, pp.674-693 
Nunez, J., X. Otazu, O. Fors, A.Prades, V, Pala, and R.Arbiol, 
1999.Multiresolution-based image fusion with addtive wavelet 
decomposition, IEEE Transactions on Geoscience and Remote 
Sensing, 37(3): 1204-1211 
.Ranchin, T. and Wald, L.,2000. Fusion of High Spatial and 
Spectral Resolution images: The ARSIS Concept and Its 
Implementation . Photogrammetric Engineering and 
RemoteSensing, 66, pp.49-61. 
Shensa. M. J.,1992.The discrete wavelet transform: Wedding 
the a Trous and Mallat algorithms, IEEE Trans. Signal Process., 
40(10), pp. 2464-2482 
Wald,L., T. Ranchin, and M. Mangolini,1997. Fusion of 
satellite images of different spatial resolution: Assessing the 
quality of resulting images, Photo-grammetric Engineering and 
Remote Sensing, 63(6),pp.691-699. 
Yocky, D.A., 1996.Multiresolution Wavelet Decomposition 
Image Merger of Landsat Thematic Mapper and SPOT 
Panchromatic Data, Photogrammetric Engineering and Remote 
Sensing, 62(3),pp. 295-303. 
Zhou.J., Civco. D. L., and Silander J. A., 1998.A wavelet 
transform method to merge Landsat TM and SPOT 
panchromatic data,” Int. J. Remote Sens., 19(4), pp. 743-757. 
1182
	        
Waiting...

Note to user

Dear user,

In response to current developments in the web technology used by the Goobi viewer, the software no longer supports your browser.

Please use one of the following browsers to display this page correctly.

Thank you.