Noisier2Inverse: Self-Supervised Learning for Image Reconstruction With Correlated Noise
We propose Noisier2Inverse, a correction-free, self-supervised deep learning method for general inverse problems. Our approach learns a reconstruction function without requiring ground truth data and is applicable in settings where measurement noise is statistically correlated. This includes applica...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11119530/ |
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