A fast 2D-AR(1) filtering for bitemporal change detection on UWB SAR images

Marcello Costa; Ingo Sander; Ingemar Söderquist; Patrik Dammert; Anders Åhlander; Christer Fuglesang

doi:10.1117/12.3030977

19 November 2024 A fast 2D-AR(1) filtering for bitemporal change detection on UWB SAR images

Marcello Costa, Ingo Sander, Ingemar Söderquist, Patrik Dammert, Anders Åhlander, Christer Fuglesang

Author Affiliations +

Proceedings Volume 13196, Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX; 131960U (2024) https://doi.org/10.1117/12.3030977
Event: Remote Sensing, 2024, Edinburgh, United Kingdom

Abstract

This article presents an elementary change detection algorithm designed using a synchronous model of computation (MoC) aiming at efficient implementations on parallel architectures. The change detection method is based on a 2D-first-order autoregressive ([2D-AR(1)]) recursion that predicts one-lag changes over bitemporal signals, followed by a high-parallelized spatial filtering for neighborhood training, and an estimated quantile function to detect anomalies. The proposed method uses a model-based on the functional language paradigm and a well-defined MoC, potentially enabling energy and runtime optimizations with deterministic data parallelism over multicore, GPU, or FPGA architectures. Experimental results over the bitemporal CARABAS-II SAR UWB dataset are evaluated using the synchronous MoC implementation, achieving gains in detection and hardware performance compared to a closed-form and well-known complexity model over the generalized likelihood ratio test (GLRT). In addition, since the one-lag AR(1) is a Markov process, its extension for a Markov chain in multitemporal (n-lags) analysis is applicable, potentially improving the detection performance still subject to high-parallelized structures.

Conference Presentation

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

Citation Download Citation

Marcello Costa, Ingo Sander, Ingemar Söderquist, Patrik Dammert, Anders Åhlander, and Christer Fuglesang "A fast 2D-AR(1) filtering for bitemporal change detection on UWB SAR images", Proc. SPIE 13196, Artificial Intelligence and Image and Signal Processing for Remote Sensing XXX, 131960U (19 November 2024); https://doi.org/10.1117/12.3030977

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