ul 2004 
lishing 
lishing 
in the 
Wuhan 
em for 
Digital 
ecord, 
[FILM 
IMAGE FUSION OF LANDSAT AND KOREAN SATELLITE KOMPSAT 
S.H Han, J.M Kang" 
“Dept. of Civil Engineering Cheonan National 
Technical College | shehan(g)entc.ac.kr 
b x ~ . . . = . . . . 
Dept. of Civil Engineering, Chungnam National University, jmkang@enu.ac.kr 
Commission I, WG 1/3 
KEY WORDS : Image fusion, Spatial resolution, Wavelet fusion, HIS 
ABSTRACT : 
Korea is providing images with the resolution of 6.6m level as launching multi-purpose satellite, Arirang satellite, in Dec. 
1999. This study analyzed advantages and disadvantages of image fusion methods as applying fusion techniques to panchromatic 
images of high resolution of Arirang satellite and multi-spectral images of LANDSAT as test images. Analysis showed that the 
wavelet image fusion technique is good for a variety of test fields. 
1. BACKGROUND AND GOALS 
This study aims to create components for fusion 
techniques for spatial information of high resolution images 
and spectral information of multi-spectral images. General 
purpose of image fusion is to produce images that can be more 
casily analyzed as enhancing spatial resolutions of low 
resolution images with spectral data. This study carried out 
creation of components as applying the method to fuse spectral 
resolution of multi-spectral images from multiple wavelength 
ranges with inferior spatial resolution and spatial resolution of 
the latest panchromatic images of high resolution such as 
IKONOS. Among fusion methods for fusing multi-spectral 
images of low resolution and high resolution, the most common 
methods are IHS(Intensity Hue Saturation), HPF(High Pass 
Filter), PCA(Principal Component Analysis) and Wavelet 
Fusion that has been recently researched a lot(Kim, 2000). 
The goal of this study is to develop a system through 
development of modules using Visual Basic and Visual C++ 
and to define algorithm for IHS and Wavelet fusion methods. 
Moreover, this study analyzes compatibility of satellite fusion 
methods as applying a developed system to  Arirang 
(KOMPSAT; KOrean Multi-Purpose SATellite) and identifying 
problems. 
2. RESEARCH 
2.1 Preparation of Test Images 
This study prepared star images(500*500) by R.G.B. band of 
Landsat and black and white images(1923*2124) of 
KOMPSAT(EOS) along the Hangang riverside. Land covers 
varies on images so that test images were selected as Landsat 
319*319 and KOMPSAT 1335*1335. Raw images were 
normalized for easy processing. Figure 1 shows the images. 
Window parts of images indicated test areas. To enhance 
readability of images, histograms were analyzed and 
normalized by band. Test areas were defined on the basis of 
KOMPSAT images with high resolutions. 
2.2 Geometric Correction of Images 
For absolute comparison between IHS and Wavelet Fusion 
method, both images were sized enough to satisfy all test 
conditions. Landsat images were generated through fusion of 
R,GB bend. Then, the geometric correction was applied to 
Landsat images as referring to KOMPSAT as reference images. 
Geometric correction of images used ERDAS Imagine 8.4. 
To this end, the reference points were set to 6 points with good 
luminance on images and the check points were set to 5 points. 
  
Figure 1 Testing area. (KOMPSAT B&W) 
The table below explains the process for geometric 
correction. If overall errors on the reference point and the check 
point were within 1 pixel, they were accepted as allowable 
errors. In preparing test images in this study, the errors was 
Table 1 Residual and RMSE of check points when Geometric 
correction 
  
  
  
Check X Y RMSE Contrib. 
point residual residual (pixel) 
7 -0.071 0.036 0.080 0.630 
8 -0.001 0.195 0.195 1.538 
9 0.031 -0.038 0.049 0.386 
10 0.009 -0.134 0.134 1.059 
11 0.004 0.175 0.175 1.385 
12 -0.009 0.027 0.029 0.225 
Avg.(ABS) 0.020 0.101 0.110 0.870 
  
about 0.13 pixel for geometric correction. Table 1 describes the 
results of correction processing. It was required to satisfy limit 
requirements to apply each fusion method. In particular, for 
wavelet method, image sizes had to be limited to 2" so that 
images were sized to 512*512 by adjustment. This study 
identified and applied the method to most effectively extract 
images with the sized of 2".