Preprints, Working Papers, ... Year : 2024

Just Project! Multi-Channel Despeckling, the Easy Way

Abstract

Reducing speckle fluctuations in multi-channel SAR images is essential in many applications of SAR imaging such as polarimetric classification or interferometric height estimation. While single-channel despeckling has widely benefited from the application of deep learning techniques, extensions to multi-channel SAR images are much more challenging. This paper introduces MuChaPro, a generic framework that exploits existing single-channel despeckling methods. The key idea is to generate numerous single-channel projections, restore these projections, and recombine them into the final multi-channel estimate. This simple approach is shown to be effective in polarimetric and/or interferometric modalities. A special appeal of MuChaPro is the possibility to apply a self-supervised training strategy to learn sensor-specific networks for single-channel despeckling.
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Dates and versions

ujm-04660707 , version 1 (19-08-2024)

Identifiers

  • HAL Id : ujm-04660707 , version 1

Cite

Loïc Denis, Emanuele Dalsasso, Florence Tupin. Just Project! Multi-Channel Despeckling, the Easy Way. 2024. ⟨ujm-04660707⟩
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