Feature Detection in Multi-Temporal Sar Images

Bujor, F.; Trouvé, E.; Valet, Lionel; Bolon, Philippe; Nicolas, Jean‐Marie; Rudant, Jean-Paul

doi:10.1142/9789812702630_0004

Cited by 1 publication

(1 citation statement)

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“…All these techniques are designed for comparison between only two SAR images. Not many works were interested to the change detection and monitoring over a time series of SAR images [8]. Most of them are feature and model based Techniques, pixel based clustering techniques or frequent sequential pattern based techniques [6].…”

Section: Introductionmentioning

confidence: 99%

Multi-Temporal Sar Change Detection and Monitoring

Hachicha

Chaâbane

2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Multitemporal SAR images are a very useful source of information for a large amount of applications, especially for change detection and monitoring. In this paper, a new SAR change detection and monitoring approach is proposed through the analysis of a time series of SAR images covering the same region. The first step of the method is the SAR filtering preprocessing step using an extension of the spatial NL-means filter to the temporal domain. Then, the Rayleigh Kullback Leibler and the Rayleigh Distribution Ratio measures are combined to detect the changes between a reference image and each SAR image of the time series at both local and global scale. These measures are combined using the Dezert-Smarandache theory which takes into account conflicts between sources and thus enhances the dual change detection results. Finally, a pixel based temporal classification is applied starting from the obtained change maps in order to describe the temporal behaviour of the covered regions.

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Section: Introductionmentioning

confidence: 99%