In
this report, we give a probabilistic model for automatic
change detection on airborne images taken with moving
cameras. To ensure robustness, we adopt an unsupervised
coarse matching instead of a precise image registration.
The challenge of the proposed model is to eliminate
the registration errors, noise and the parallax artifacts
caused by the static objects having considerable height
(buildings, trees, walls etc.) from the difference image.
We describe the background membership of a given image
point through two different features, and introduce
a novel three-layer Markov Random Field (MRF) model
to ensure connected homogenous regions in the segmented
image.
