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Image restoration for fluorescence microscopy using optimal sparsity and camera modeling

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Abstract

In fluorescence microscopy, the quality of the acquired images determines the extent of observable biological phenomena. To address the different noise sources degrading these images, we introduce a model-based framework compatible with several microscopy systems independently from the detector used.

© 2023 The Author(s)

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Poster Presentation

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