Elsevier

Procedia Computer Science

Volume 80, 2016, Pages 2348-2352
Procedia Computer Science

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

https://doi.org/10.1016/j.procs.2016.05.438Get rights and content
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Abstract

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.

Keywords

Probabilistic Change Detection
Satellite Image Processing
Spatial Data Mining
Sliding Window
GMM

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Selection and peer-review under responsibility of the Scientific Programme Committee of ICCS 2016.