The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
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multi-spectrum image and full-color image fusion system are as 
shown in Figure 1. 
3. WEIGHTING IMAGE FUSION BASED ON 
WAVELET TRANSFORMATION 
The fusion method based on the wavelet transformation has 
retained and inherited the main merits of tower-shaped 
transformation fusion method [2-4]. Simultaneously, because 
the orthogonal wavelet transformation has non-redundancy, the 
image data quantity after wavelet transformation will not 
increase. By using the direction of wavelet transformation, a 
better visual effect of fusion image will be able to obtain based 
on the vision characteristics that the human eye have different 
resolutions to high frequency component of different directions. 
3.1 Image fusion based on wavelet transformation 
The image fusion realization requests to extract information 
(details) from each source image and obtains the effective 
demonstration in the final fusion image. According to the 
general theory of imagery processing, the image information 
(details) is concluded in the image high frequency component, 
therefore, the key point of image fusion research is to seek an 
Image A 
Raw imagery after Multi-dimensional 
matching resolution 
Figure2 Procedure of wavelet multi-dimensional fusion 
(1) Carry on the wavelet transformation separately to each 
source image to establish various images of the wavelet tower 
shaped transformation. 
(2) Carry on fusion processing separately to each 
transformation level and to different frequency components of 
each transformation level using different fusion operator, to 
finally obtain fusion wavelet pyramid. 
(3) Carry on the wavelet inverse transformation (i.e. to carry on 
image restructuring) to wavelet pyramid after fusion to obtain 
restructuring image namely for fusion image. 
When fusing the multi-spectrum image and the high spatial 
resolution image, David proposed one method (which was 
afterwards called the WT method), which simultaneously 
carries on the wavelet transformation to the multi-spectrum 
image and the high spatial resolution image, combines the low 
frequency component of multi-spectrum image with the high 
frequency component of high spatial resolution image, then 
carries on the wavelet inversion, and finally obtains a multi 
spectrum image of the high spatial resolution. That is the initial 
wavelet transformation fusion law [5]. 
appropriate processing method of fusing detailed information of 
source image respectively, that is, how will the information be 
fuse-processed effectively in the corresponding frequency band. 
According to the multi-resolution analysis theory, the source 
image after the wavelet transformation, the inner tube signal 
row Z)j j ,Dj.j , Dj j, contains separately the image high 
frequency component of corresponding frequency directed in 
normal, horizontal and 45° of the image, therefore, using the 
image tower-shaped structure after wavelets decomposing, to 
carry on fusion processing separately according to different 
transformation level and different frequency band, the 
information detail from different images can be fused 
effectively. 
Carry on N wavelet transformation to the two-dimensional 
picture, and it will finally get some (3N+1) different frequency 
bands, which contains a 3N high frequency bands and a low- 
frequency band. The image fusion program based on wavelet 
multi-dimensional transformation is shown as in Figure 2. Take 
two image fusions as an example, many image fusion methods 
may be analogized from this regarding. Suppose A and B are 
two primitive images, F is the image after fusion, its basic 
fusion steps are as follows: 
Image F 
Wavelet 
► 
inverse 
transforrr 
Imagery 
after fusion 
In practical application, in order to prevent the spectrum 
distortion caused by replacement in the fusion process, it is 
necessary to enlarge various relevance of wave bands image 
before the transformation wavelet through the histogram 
matched various wave band images, to reduce the spectrum 
deviation of fusion image. 
The WT method is always considered as the superior high 
resolution and the multi-spectrum image fusion method. But it 
has also a shortcoming: Because the wavelet transformation has 
localization in the good air zone and the frequency range, it 
may well retain the spectrum information in the multi-spectrum 
image, but because this method has discarded low frequency 
component of the high spatial resolution image, it results in the 
ringing effect in the inverse transformation. 
3.2 Weighting image fusion algorithm based on wavelet 
transformation 
As we know, the spatial variation surface of the remote sensing 
image grey level expresses has the characteristics of stochastic 
changes. But analyzed from the spatial frequency spectrum 
angle, they may all be transformed to the spectrum which is 
composed of different spatial frequency spectrum waves.