deepmr.prox.llr_denoise#
- deepmr.prox.llr_denoise(input, ndim, ths, W, S=None, rand_shift=True, axis=None, device=None)[source]#
Apply Local Low Rank denoising.
The solution is available in closed-form, thus the denoiser is cheap to compute.
- deepmr.prox.S#
Patch stride (assume isotropic). If not provided, use non-overlapping patches.
- Type:
int, optional
- deepmr.prox.rand_shift#
If True, randomly shift across spatial dimensions before denoising.
- Type:
bool, optional
- deepmr.prox.axis#
Axis assumed as coefficient axis (e.g., coils or contrasts). If not provided, use first axis to the left of spatial dimensions.
- Type:
bool, optional
- deepmr.prox.device#
Device on which the wavelet transform is computed. The default is
None
.- Type:
str, optional
- Returns:
output – Denoised image of shape (…, n_ndim, …, n_0).
- Return type:
np.ndarray | torch.Tensor