3.2 Automated Acquisition of Tie Points
In the block adjustment method used in photogrammetry, tie point information is needed. Tie points are permanent information and we can get these data automatically. On the other hand, we have to develop efficient method in order to save the time.
Then we developed this method especially focused on quality and efficiency. (See Fig.2)
Figure 2 Flow of the Automated Acquisition of Tie Points
Tie point is the connecting (same location) point between two images. We used image correlation method used in stereo matching, because these images were acquired in different dates, and different solar angle etc. So with the method of sequential Similarity Detection Algorithm (SSDA) Method, we can not get good result, In order to check the quality and efficiency, we test the relation between template size, correlation function and calculating time.
We changed template size 7*7, 9*9, 11*11, 13*13, 15*15, 17*17, 19*19 and showed required time as 9*9 equal to 1. In 7*7 required time is good, but the quality is not much good. That is what we used 9*9 as a template size. (Graph.1)
Next, we picked up 20 scenes randomly, and checked the difference between automated method and traditional (labor demanding) method.
Graph 1 Relation between template size, correlation function and calculating time
Graph 2 shows it's result. As a result, in tie point automated acquisition, we set 9*9 as a template size and correlation function more than 0.85.
Graph 2 Difference between visual and automated tie point acquisition
3.3 Ground Control Point (GCP) Automated Acquisition
GCP acquisition is to give the location information to the satellite image using World Data Bank (WDB), Digital Chart of the World (DCW) and so on. In this process we use the information of coastal line or branch point of river because it is easy to identify in the satellite image. Here we used such water area's edge information for automated matching and giving location information.
To enhance water area in satellite images, we have five processes i.e.
- Make a Normalized Differential Vegetation Index (NDVI) image
- Detect edge of the water using level slice
- Edge enhance
- Remote Noise
- Thinning the edge
