The analysis of changes occurred in multi-temporal images acquired by the same sensor on the same geographical
area at different dates is usually done by performing a comparison of the two images after co-registration. When
one considers very high resolution (VHR) remote sensing images, the spatial information of the pixels becomes
very important and should be included in the analysis. However, taking into account spatial features for change
detection in VHR images is far from being straightforward, due to effects such as seasonal variations, differences
in illumination condition, residual mis-registration, different acquisition angles, etc., which make the comparison
of the structures in the scene complex to achieve from a spatial perspective. In this paper we propose a change
detection technique based on morphological Attribute Profiles (APs) suitable for the analysis of VHR images.
In greater detail, this work aims at detecting the changes occurred on the ground between the two acquisitions
by comparing the APs computed on the image of each date. The experimental analysis has been carried out on
two VHR multi-temporal images acquired by the Quickbird sensor on the city of Bam, Iran, before and after
the earthquake occurred on Dec. 26, 2003. The experiments confirm that the APs computed at different dates
show different behaviors for changed and unchanged areas. The change detection maps obtained by the proposed
technique are able to detect changes in the morphology of the correspondent regions at different dates regardless
their spectral variations.