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Self-Supervised Multibeam Sonar Restoration via Coherent Forward Modeling

Zixin Wang, James Hopgood, Mike Davies · 2026 · arXiv

DOI: 10.48550/arXiv.2610.31490 · open-access PDF

Abstract

Multibeam imaging sonar produces intensity images degraded by coherent speckle and system-induced blur, while clean reflectivity targets are rarely available. Existing despeckling methods often rely on simplified intensity-domain noise models, synthetic clean targets, or blind-spot self-supervision, and typically do not jointly model deblurring and speckle suppression. We propose a physics-consistent self-supervised framework for joint despeckling and deblurring of multibeam imaging sonar. A stochastic coherent image-formation model yields a conditional-mean forward operator that relates laten

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