Proximal Operators#
Sub-package containing regularization routines.
DeepMR provides regularization routines for plug-n-play compressed sensing.
Classical Denoisers#
Classical (i.e., non-trainable) denoisers can be used inside iterative reconstructions as regularizars (aka, PnP reconstruction).
DeepMR expose denoisers both as torch.nn
objects (to be chained in DL-based reconstructions)
and functional forms (e.g., for simple standalone denoising).
Currently available denoisers are Wavelet (WaveletDenoiser
, WaveletDictDenoiser
),
Local Low Rank (LLRDenoiser
) and Total (Generalized) Variation (TVDenoiser
, ``TGVDenoiser`).
Both WaveletDenoiser
/ WaveletDictDenoiser
and TVDenoiser
/ TGVDenoiser
are adapted for complex-value inputs from the corresponding DeepInverse implementations.
Orthogonal Wavelet denoising with the \(\ell_1\) norm. |
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Overcomplete Wavelet denoising with the \(\ell_1\) norm. |
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Proximal operator of the isotropic Total Variation operator. |
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Proximal operator of (2nd order) Total Generalised Variation operator. |
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Local Low Rank denoising. |
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Apply overcomplete Wavelet denoising with the \(\ell_1\) norm. |
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Apply orthogonal Wavelet denoising with the \(\ell_1\) norm. |
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Apply isotropic Total Variation denoising. |
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Apply Total Generalized Variation denoising. |
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Apply Local Low Rank denoising. |