Self-Supervised SAR Despeckling Using Deep Image Prior

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Chiara Albisani, Daniele Baracchi, Alessandro Piva, Fabrizio Argenti

Published: 01 Jan 2025, Last Modified: 07 Nov 2025Pattern Recognit. Lett. 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•A self-supervised learning method for SAR despeckling, denoted as S3DIP, is proposed.•The Deep Image Prior (DIP) approach is extended introducing a learnable noise matrix.•A histogram loss based on the knowledge of the speckle noise statistics is designed.•Existing model-based denoisers are exploited through the use of a guidance loss.•S3DIP outperforms both DIP and existing model-based denoisers on the intended task.