Automatic Database Development Methods for a very Large Number of Satellite Images
2.1.2.3 Automated Acquisition of Ground Control point (GCP)
GCP acquisition is for determining the exact location of satellite images on digital maps of a given coordinate system like world Data Bank (WDB), Digital Chart of the World (DCW). In this process we use the information of coastal line or branch point of river system as GCPs, because it is easy to identify them in the satellite images.
To enhance water area in satellite images, we have five processes as follows .
-
Genertrate a Normalized differential Vegetation Index (NDVI) images
- Detect edge of the water level slicing .
- Enhance Edge
- Remove Noise
- Thinning the Edge
On the other hand, by using DCW, we generater the library of GCP template images. With Sequential Similarity Detection Algorithm (SSDA), we determine matching points between the GCP template images and extracted coastal line etc. result shows that with this method , we can get a high quality results for the coastal line, but not for the river in land .
Fig .3 GCP acquisition method
2.1.2.4 Simultaneous adjustment of Images using Block Adjustment Method in photogrammetry
Using the technique of block adjustment in photogarmmetry, that is, using the tie points and the GCPs, by minimizing the error
e(shown below ), we can estimate all parameters for geometric for all images simultaneously .
Fig 4. Block adjustment method
2.2 Proposed resampling method and spatial representation of images/raster data.
It is very important to fuse different satellite sensor images with different resolutions for earth environmental studies. In fusing or overlaying images or transforming images or transforming images onto a coordinate system. It requires to identify exact inclusion relationship between pixels and grid cells. However, in the implementation of the resampling, center position of each grid cell is transferred ot the images plane. And a pixel including transformed center point is regarded as a pixel corresponding the grid cell, which may fail to identify exact coupling relations ]especially when the grid cell size is much larger than the pixels on the ground. This comes from the footprint of pixels on the ground is not represented explicitly. Future, Resampling is computationally heavy ( a bottleneck ). In this research, to solve these problems, we propose a new resampling method together with the data model.
Fig 5. Problems in resampling
