A robust nonlinear scale space change detection approach for SAR images

Berk Sevilmis, Osman Erman Okman, Fatih Nar, Can Demirkesen, Müjdat Çetin, Lorenzo Bruzzone
2013 Image and Signal Processing for Remote Sensing XIX  
In this paper, we propose a change detection approach based on nonlinear scale space analysis of change images for robust detection of various changes incurred by natural phenomena and/or human activities in Synthetic Aperture Radar (SAR) images using Maximally Stable Extremal Regions (MSERs). To achieve this, a variant of the log-ratio image of multitemporal images is calculated which is followed by Feature Preserving Despeckling (FPD) to generate nonlinear scale space images exhibiting
more » ... nt trade-offs in terms of speckle reduction and shape detail preservation. MSERs of each scale space image are found and then combined through a decision level fusion strategy, namely "selective scale fusion" (SSF), where contrast and boundary curvature of each MSER are considered. The performance of the proposed method is evaluated using real multitemporal high resolution TerraSAR-X images and synthetically generated multitemporal images composed of shapes with several orientations, sizes, and backscatter amplitude levels representing a variety of possible signatures of change. One of the main outcomes of this approach is that different objects having different sizes and levels of contrast with their surroundings appear as stable regions at different scale space images thus the fusion of results from scale space images yields a good overall performance. Downloaded From: http://proceedings.spiedigitallibrary.org/ on 10/27/2013 Terms of Use: http://spiedl.org/terms Proc. of SPIE Vol. 8892 889215-2 Downloaded From: http://proceedings.spiedigitallibrary.org/ on 10/27/2013 Terms of Use: http://spiedl.org/terms
doi:10.1117/12.2030189 fatcat:ah3fav3wxved5lplnxfwcygspe