Please use this identifier to cite or link to this item:
https://dspace.univ-adrar.edu.dz/jspui/handle/123456789/4176
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | MOUSSELMEL, ZOHRA | |
dc.contributor.author | HOUTIA, Cherifa | |
dc.contributor.author | OUAHAB, Abdelwhab / Promoteur | |
dc.date.accessioned | 2020-10-26T09:52:01Z | |
dc.date.available | 2020-10-26T09:52:01Z | |
dc.date.issued | 2020-10-14 | |
dc.identifier.uri | https://dspace.univ-adrar.edu.dz/jspui/handle/123456789/4176 | |
dc.description | Option : Systèmes intelligents | en_US |
dc.description.abstract | Change detection is an integral part of the analysis of satellite imagery, and it has been studied for several decades. It consists of comparing a registered pair of images of the same region and identifying the parts where a change has occurred, it allow to follow the evolution over time of a region of interest through technical changes upon detection So these images are a tool of choice in the management of natural resources. This requires a methodological approach appropriate image processing to the use of such data. In this work we compared the performance of three methods (Difference, ACP-Kmeans, Logmean) for the detection of changes in satellite images using the different evaluation metrics (FA, DR, Kappa, Precision, Recall, TC), and we were found that the ACP-Kmeans method gives a binary DC mask with better precision compared to other method. | en_US |
dc.description.abstract | Change detection is an integral part of the analysis of satellite imagery, and it has been studied for several decades. It consists of comparing a registered pair of images of the same region and identifying the parts where a change has occurred, it allow to follow the evolution over time of a region of interest through technical changes upon detection So these images are a tool of choice in the management of natural resources. This requires a methodological approach appropriate image processing to the use of such data. In this work we compared the performance of three methods (Difference, ACP-Kmeans, Logmean) for the detection of changes in satellite images using the different evaluation metrics (FA, DR, Kappa, Precision, Recall, TC), and we were found that the ACP-Kmeans method gives a binary DC mask with better precision compared to other method. | |
dc.language.iso | fr | en_US |
dc.publisher | universite Ahmed Draia-ADRAR | en_US |
dc.subject | Systèmes intelligents | en_US |
dc.subject | informatique | en_US |
dc.subject | télédétection | en_US |
dc.subject | image satellitaire | en_US |
dc.subject | détection des changements | en_US |
dc.subject | : Change detection, satellite image, remote sensing | en_US |
dc.title | Détection des changements dans les images satellitaires | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | Mémoires de Master |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Détection des changements dans les images satellitaires.pdf | 3.31 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.