Sliding Window-based Probabilistic Change Detection for Remote-sensed Images

A recent probabilistic change detection algorithm provides a way for assessing changes on remote-sensed images which is more robust to geometric and atmospheric errors than existing pixel-based methods. However, its grid (patch)-based change detection results in coarse-resolution change maps and oft...

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Bibliographic Details
Published inProcedia computer science Vol. 80; pp. 2348 - 2352
Main Authors Hong, Seokyong, Vatsavai, Ranga R.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2016
Subjects
GMM
Probabilistic Change Detection
Satellite Image Processing
Sliding Window
Spatial Data Mining
Probabilistic Change Detection
Sliding Window
Spatial Data Mining
Satellite Image Processing
GMM
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Summary:A recent probabilistic change detection algorithm provides a way for assessing changes on remote-sensed images which is more robust to geometric and atmospheric errors than existing pixel-based methods. However, its grid (patch)-based change detection results in coarse-resolution change maps and often discretizes continuous changes that occur across grid boundaries. In this study, we propose a sliding window-based extension of the probabilistic change detection approach to overcome such artificial limitations.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2016.05.438