Annual Report 2009/2010 - JUWEL - Forschungszentrum Jülich
Annual Report 2009/2010 - JUWEL - Forschungszentrum Jülich
Annual Report 2009/2010 - JUWEL - Forschungszentrum Jülich
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Fig. 124: Segmentation using local mutual best fitting test and global segment removal of two<br />
scenes with simulated changes using parameters T = 75, T check = 75, T checktolerance = 0.5,<br />
w s = 0.1 and w comp = 0.5.<br />
Fig. 125: Segmentation using local best fitting test and local segment removal of two scenes<br />
with simulated changes using parameters T = 75, T check = 75, T checktolerance = 0.5, w s = 0.1<br />
and w comp = 0.5.<br />
Conclusion<br />
We presented some new ideas for addressing the issue of segmenting remote sensing<br />
imagery for object-based change detection. An enhanced procedure based on<br />
multiresolution segmentation was presented, and it was shown that satisfying results for<br />
simulated data can be achieved.<br />
Further developments are needed such as new consistency tests and segment removal<br />
strategies. Moreover, methods for enabling the user to easily select the segmentation<br />
parameters, e.g. by using training samples, would be helpful. Finally, the adapted<br />
multiresolution segmentation needs to be implemented as eCognition plugin for allowing its<br />
direct use in the proposed change detection workflow.<br />
References<br />
[1] A. Singh, Review Article Digital change detection techniques using remotely-sensed data, International<br />
Journal of Remote Sensing 10, 6 (1989) 989-1003.<br />
[2] R. Radke, S. Andra, O. Al-Kofahi, Image change detection algorithms: a systematic survey, IEEE<br />
Transactions on Image Processing 14, 3 (2005) 294-307.<br />
[3] M. J. Canty, Image Analysis, Classification, And Change Detection In Remote Sensing: With Algorithms<br />
For ENVI/IDL, Taylor & Francis Ltd, 2nd ed. (<strong>2009</strong>).<br />
[4] T. Blaschke, S. Lang, and G. Hay (Eds.), Object-Based Image Analysis Spatial Concepts for Knowledge-<br />
Driven Remote Sensing Applications, Series: Lecture Notes in Geoinformation and Cartography,<br />
Springer, Berlin (2008).<br />
[5] I. Niemeyer, P. R. Marpu, and S. Nussbaum, Change detection using object features, Blaschke, T.,<br />
Lang, S. & Hay, G. (Eds.), Object-Based Image Analysis Spatial Concepts for Knowledge-Driven<br />
Remote Sensing Applications, Series: Lecture Notes in Geoinformation and Cartography, Springer,<br />
Berlin (2008) 185-201.<br />
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