A Framework for Robust 3-D Change Detection
by Heller, A. J. and Leclerc, Y. G. and Luong, Q.-T.
in Proceedings of the International Symposium on Remote SensingAddress: Toulouse, France
We present an application of our framework for 3-D object-centered change detection to combined satellite and aerial imagery. In this framework, geometry is compared to geometry, allowing us to compare image sets with different acquisition conditions and even different sensors. By working in this framework, we do not encounter the restrictions and short-comings of conventional image-based change detection, which requires that the images being compared have similar acquisition geometry, photometry, scene illumination, and so forth.
The contributions of our framework are: (1) using a geometric basis for change detection, allowing image sets acquired under different conditions to be compared; (2) explicit modeling of image geometry to be able to numerically characterize significant and insignificant change. The contributions of this paper are: (1) the algorithms are embedded in an integrated cartographic modeling and image processing system, which can ingest and make use of a variety of government and commercial imagery and geospatial data products; (2) experimentation with a variety of imagery and scene content.
Modifications to the algorithms specific to their use with satellite imagery are discussed and the results from several experiments with both aerial and satellite images urban domains are described and analyzed.
|Heller, Aaron J||Principal Scientist|
|Leclerc, Yvan G||Alumnus|