Change Detection for High Resolution Satellite Images, based on SIFT descriptors and an a Contrario approach

Abstract : 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 lim- ited. It is often needed to compare images acquired by different sensors and with different acquisition condi- tions. 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.
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Flora Dellinger, Julie Delon, Yann Gousseau, Julien Michel, Florence Tupin. Change Detection for High Resolution Satellite Images, based on SIFT descriptors and an a Contrario approach. IGARSS 2014, Jul 2014, Québec, Canada. ⟨hal-01059366⟩

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