Leveraging structural information for enhanced coherent change detection

Scott Dayton; Oliver Milledge; Jovana Nikitovic; Anne Gelb; Dylan Green; Aditya Viswanathan

doi:10.1117/12.3016301

7 June 2024 Leveraging structural information for enhanced coherent change detection

Scott Dayton, Oliver Milledge, Jovana Nikitovic, Anne Gelb, Dylan Green, Aditya Viswanathan

Proceedings Volume 13032, Algorithms for Synthetic Aperture Radar Imagery XXXI; 130320C (2024) https://doi.org/10.1117/12.3016301
Event: SPIE Defense + Commercial Sensing, 2024, National Harbor, Maryland, United States

Abstract

We consider the two-pass coherent change detection problem for SAR imaging. Inspired by classical maximum likelihood-based coherent change detectors (Jakowatz, 1996) and multi-polarization SAR change detection techniques (Novak, 2005), we propose a method of incorporating underlying structural image information using specially formulated kernels. In particular, we utilize a class of convolutional edge detection kernels to extract underlying edge information in the scene of interest given noisy and potentially incomplete data. We then adapt existing multi-polarization SAR change detection methods to incorporate such edge information to improve the quality and robustness of resulting change maps. We validate the proposed method using real-world SAR images from the CCD Challenge Problem dataset and demonstrate improved change detection performance using empirical ROC studies.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Scott Dayton, Oliver Milledge, Jovana Nikitovic, Anne Gelb, Dylan Green, and Aditya Viswanathan "Leveraging structural information for enhanced coherent change detection", Proc. SPIE 13032, Algorithms for Synthetic Aperture Radar Imagery XXXI, 130320C (7 June 2024); https://doi.org/10.1117/12.3016301

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