Performance estimation of similarity measures of multi-sensor images for change detection applications

V. Alberga, M. Idrissa, V. Lacroix, J. Inglada

Résultats de recherche: Chapitre dans un livre, un rapport, des actes de conférencesContribution à une conférenceRevue par des pairs

Résumé

Change detection of remotely sensed images is a particularly challenging task when the available data come from different sensors. Indeed, many change indicators are based on radiometry measures, operating on them differences or ratios, that are no longer reliable when the data have been acquired by different instruments. For this reason, it is interesting to study the performance of those indicators that do not rely completely on radiometric values. A series of similarity measures for automatic change detection was investigated and their performance compared using optical and SAR images covering a period of several years. We could observe that the considered change detection algorithms perform differently but that none of them permits an "absolute" measure of the changes independent of the sensor.

langue originaleAnglais
titreProceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images
Les DOIs
étatPublié - 2007
Evénement2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007 - Leuven, Belgique
Durée: 18 juil. 200720 juil. 2007

Série de publications

NomProceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images

Une conférence

Une conférence2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007
Pays/TerritoireBelgique
La villeLeuven
période18/07/0720/07/07

Empreinte digitale

Examiner les sujets de recherche de « Performance estimation of similarity measures of multi-sensor images for change detection applications ». Ensemble, ils forment une empreinte digitale unique.

Contient cette citation