Automatic Precision Correction of Satellite Images
using the Chips of Different Resolution
2. METHODS AND EXPERIMENT DATASET
The main process of this research can be composed of two procedures. Firstly, we found
correspond points in Landsat-7 image using the GCP chips of IKONOS GEO level image with
in-house automatic precision algorithms. And then we corrected precisely KOMPSAT-1 EOC
image from Landsat-7 panchromatic image and DEM. Below figure 1 shows that the procedure of
this study. White dot on figure 1 is test site.
Figure 1. Procedure of automatic precision correction for KOMPSAT-1 EOC image
Below is the detail step for precision correction of KOMPSAT-1 image using IKONOS and
Landsat-7 image.
- Step 1: IKONOS image is downsampled to Landsat-7 Resolution
- Setp 2: Generate GCP chips from downsampled IKONOS image
- Setp 3: Matching between GCP chips from IKONOS image and Landsat-7 panchromatic image
- Setp 4: Generate GCP chips from Landsat-7 image using matching result and DEM
- Setp 5: Matching between GCP chips from Landsat-7 image and KOMPSAT-1 image
- Setp 6: Precision correction of KOMPSAT-1 image
In step 1, because there are a lot of difference between the resolution of IKONOS and the ground
sample distance of Landsat-7, we did downsample IKONOS GEO image to Landsat-7 image
using nearest-neighbor and cubic convolution and tested for each images. Also, after we did
downsample IKONOS GEO image using nearest-neighbor, we adjust IKONOS image Landsat-7
image using lowpass filter and histogram matching and tested for this.
In step 2, we will extract the geological information in previously generated IKONOS GEO image
and DEM. To compare with human operator, we also used geological coordinate from GPS
survey. Figure 1 shows the GCPs on the IKONOS image from GPS Survey.
In step 3, we found the correspondence points on Landsat-7 image with in-house matching
algorithms for previously GCP chips. In this stage, we will show the results that our in-house
algorithms are effectively removed from the extracted control points so that image image
registration and precise image correction can be accurately performed.
Next, In step 4 and step 5, we generated the GCP chips from Landsat-7 image using previously matching results and
DEM. We used DEM to extract height information. Finally, we did precisely correct
KOMPSAT-1 EOC image using the GCP chips from Landsat-7 image.
For experiments in this paper, three types of satellite images were used. Table 1 summarizes the
characteristics of each image and ground control points that used in GCP chips. The first one was
level Geo image of IKONOS panchromatic image. The second one was level 1G image of
Landsat-7. The ground sampling distance of Landsat-7 panchromatic image is 15m. The third one
was target image from KOMPSAT-1 image to precisely correct. The test site we selected was
“Bundang” city of the Republic of Korea.
Table 1. The characteristics of satellite image used for experiments
