Change detection for high resolution satellite images, based on SIFT descriptors and an a contrario approach

In disaster situations, remote sensing images are very useful to quickly assess damages. However, the choice of available images for the studied area is frequently limited. It is often needed to compare images acquired by different sensors and with different acquisition conditions. We propose a new feature-based approach to detect changes between a pair of either optical or radar images. This approach is based on the SIFT algorithm and an a contrario approach. It can deal with multi-resolutions, multi-sensors and multi-incidence angles situations, and it offers promising results.