A contrario comparison of local descriptors for change detection in Very High spatial Resolution (VHR) satellite images of urban areas - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Geoscience and Remote Sensing Year : 2018

A contrario comparison of local descriptors for change detection in Very High spatial Resolution (VHR) satellite images of urban areas

(1) , (2) , (2)
1
2
Gang Liu
  • Function : Author
  • PersonId : 1013365
Yann Gousseau

Abstract

Change detection is a key problem for many remote sensing applications. In this paper, we present a novel unsupervised method for change detection between two high resolution remote sensing images possibly acquired by two different sensors. This method is based on keypoints matching, evaluation and grouping, and does not require any image co-registration. It consists of two main steps. First, global and local mapping functions are estimated through keypoints extraction and matching. Secondly, based on these mappings, keypoint matchings are used to detect changes and then grouped to extract regions of changes. Both steps are defined through an {\it a contrario} framework, simplifying the parameter setting and providing a robust pipeline. The proposed approach is evaluated on synthetic and real data from different optic sensors with different resolutions, incidence angles and illumination conditions.
Fichier principal
Vignette du fichier
Changedet_TGRS_final.pdf (39.56 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01739459 , version 1 (21-03-2018)
hal-01739459 , version 2 (19-12-2018)

Identifiers

Cite

Florence Tupin, Gang Liu, Yann Gousseau. A contrario comparison of local descriptors for change detection in Very High spatial Resolution (VHR) satellite images of urban areas. IEEE Transactions on Geoscience and Remote Sensing, In press, ⟨10.1109/TGRS.2018.2888985⟩. ⟨hal-01739459v2⟩
254 View
110 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More