Artifact Removal

The simplest method for reconstructing an image from a measurements is to first map the measurements to the image domain via a non-learned mapping, and then apply a denoiser network to the obtain the final reconstruction.

The deepinv.models.ArtifactRemoval class converts a denoiser deepinv.models.Denoiser or other image-to-image network \(\phi\) into a reconstruction network deepinv.models.Reconstructor \(R\) by doing

• Adjoint: \(\inversef{y}{A}=\phi(A^{\top}y)\) with mode='adjoint'.

  This option is generally to linear operators \(A\).

• Pseudoinverse: \(\inversef{y}{A}=\phi(A^{\dagger}y)\) with mode='pinv'.

• Direct: \(\inversef{y}{A}=\phi(y)\) with mode='direct'.

  This option serves as a wrapper to obtain a Reconstructor, and can be used to adapt a generic denoiser or image-to-image network into one that is specific to an inverse problem.