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vertical components of each shifting vector
respectively. To each of the clusters in Px-Py space,
we find the cluster center, or median vector, with
which every member of the cluster should go along.
4. Experimental Results
To test our algorithms, we have simulated the Nojima fault,
which accompanied the great Hanshin-Awaji earthquake of
1995 in Japan. The model has been constructed with a
rectified image which has been oriented by
photogrammetric approach. Firstly, the shifting amount in
the real world coordinates is specified. Then the shifting
amount in image coordinates is calculated for the
designated fault area. Lastly, move one side of the
simulated fault along its direction by the calculated amount
- in Nojima’s case both 1m in planar and horizontal as
shown in Fig.3 (b). This model cannot ensure a uniform
shift amount within the shifted area. Yet in this case the
differences are negligible since the simulated area is very
small when compared with the original image.
With the pair images Fig.3(a);before the fault, and (b);after
the fault, we applied the bi-cluster approach, to find out the
fault boundary successfully as shown in Fig.3(c).
5. Conclusion
By introducing the new consensus operations into our
nonlinear mapping technique, we were able to detect the
simulated fault from a pair of aerial images. Since this
technique uses a self-organizing nonlinear mapping based
on the principle of coincidence enhancement, differences
in the image distortion and non-equalized quality between
two images can be automatically compensated for [3].
This work was partly supported by JST, Japan.
References:
[1] Y. Kosugi, P. Tchimev, M. Fukunishi, S. Kakumoto and
T. Doihara: An Adaptive Nonlinear Mapping Technique for
Extracting Geographical Changes; Proc. GIS2000 /
CD-ROM; 4pages (2000)
[2] M. Matsuoka and F. Yamazaki: Use of Interferometric
Satellite SAR for Earthquake Damage Detection, Proc. 6 th .
Conf. Seismic Zonation (2000)
[3] Y. Kosugi, M. Sase, H. Kuwatani et a!.: Neural Network
Mapping for Nonlinear Stereotactic Normalization of Brain
MRI mages, J. Comp. Ass. Tomogra., Vol.17, No.3,
445-460 (1993)
(a) before earthquake (b)after earthquake (c) detected dislocation
Fig.3 Automatically detected dislocation from a set of aerial photo images simulating the Nojima fault related to the
great Hanshin-Awaji earthquake.
