SEMANTIC INTERPRETATION OF MULTI-LEVEL CHANGE DETECTION IN MULTI-TEMPORAL SATELLITE IMAGES

被引：0

作者：

Radoi, A. ^{[1
]}

Tanase, R. ^{[1
,2
]}

Datcu, M. ^{[1
,3
]}

机构：

[1] UPB, Bucharest, Romania

[2] Mil Tech Acad, Bucharest, Romania

[3] German Aerosp Ctr DLR, Remote Sensing Technol Inst, Oberpfaffenhofen, Germany

来源：

2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2015年

关键词：

Multispectral images; change detection; binary descriptors; Mean-Shift;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Satellite image time series are a valuable resource for enhancing land exploitation by respecting the natural cycles, analyzing urban expansion and its positive and negative effects, limiting the unhealthy rhythm of deforestation, understanding natural hazards and so on. In this context, understanding only the changes in multitemporal images is not sufficient. This paper aims to correlate multi-level change detection techniques with image semantic segmentation methods in order to build an hierarchy of changes for each semantic class. In this way, we are able to provide statistics regarding the levels of change suffered by a certain area. The methods are demonstrated with examples involving bi-temporal Landsat images.

引用

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页码：4157 / 4160

页数：4

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