@inproceedings{3b2c09329d124e8aa51dd9a48cc74ee8,
title = "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 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.",
keywords = "RANSAC, SAR image, SIFT, a contrario methods, change detection, image comparison, local descriptors",
author = "Flora Dellinger and Julie Delon and Yann Gousseau and Julien Michel and Florence Tupin",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; Joint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 ; Conference date: 13-07-2014 Through 18-07-2014",
year = "2014",
month = nov,
day = "4",
doi = "10.1109/IGARSS.2014.6946667",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1281--1284",
booktitle = "International Geoscience and Remote Sensing Symposium (IGARSS)",
}