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Remote sensing technology plays an important role in gathering information of social infrastructure damage which is crucial for relief and reconstruction work after strike. Comparatively speaking, radar sensors are capable of observing the ground irrespective of weather conditions or the time of the day, and therefore have been gaining prominence as a reliable tool for grasping the overall picture...
In this paper, we present a new framework for building change detection from monocular aerial imagery that automatically predicts building candidates based on adaptive local textural features with successive background removal. An adaptive local entropy feature is developed based on quadratic regression and Random Sample Consensus (RANSAC) for extracting potential building candidates. Then a majority...
This paper presents change detection using very high resolution SAR data. Small patches of SAR data were used for graphical Lasso based algorithm. The graphical Lasso for time series is defined as solution of an l1-regularized maximum likelihood problem. The optimization problem was solved using alternating direction method of multipliers (ADMM). The time series of patches was observed. The efficiency...
This paper presents a method for strong scatterers change detection in synthetic aperture radar (SAR) images based on a decomposition for multi-temporal series. The formulated decomposition model jointly estimates the background of the series and the scatterers. The decomposition model retrieves possible changes in scatterers and the date at which they occurred. An exact optimization method of the...
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