spyrit.core.recon.DCNet.reconstruct

DCNet.reconstruct(y: tensor) → tensor

Reconstruct an image from measurements.

This method sucessively applies the preprocessing operator prep, the Tikhonov regularization operator tikho, and the denoising operator denoi to the input measurement vectors x.

Args:

y: raw measurement vectors with shape \((b, c, M)\)

Returns:

torch.tensor: Reconstructed images with shape \((b,c,h,w)\)

Example:

>>> from spyrit.core.meas import HadamSplit2d
>>> from spyrit.core.prep import UnsplitRescale
>>> from spyrit.core.recon import DCNet
>>> import torch
>>> acqu = HadamSplit2d(32)
>>> prep = UnsplitRescale()
>>> sigma = torch.eye(32*32,32*32)
>>> dcnet = DCNet(acqu, prep, sigma)
>>> y = torch.randn(10, 1, 2048)
>>> z = dcnet.reconstruct(y)
>>> print(z.shape)
torch.Size([10, 1, 32, 32])