pytomography.transforms.shared.filters#

Module Contents#

Classes#

GaussianFilter

Applies a Gaussian smoothing filter to the reconstructed object with the specified full-width-half-max (FWHM)

class pytomography.transforms.shared.filters.GaussianFilter(FWHM)[source]#

Bases: pytomography.transforms.Transform

Applies a Gaussian smoothing filter to the reconstructed object with the specified full-width-half-max (FWHM)

Parameters:

FWHM (float) – Specifies the width of the gaussian

configure(object_meta, proj_meta)[source]#

Configures the transform to the object/proj metadata. This is done after creating the network so that it can be adjusted to the system matrix.

Parameters:
  • object_meta (ObjectMeta) – Object metadata.

  • proj_meta (ProjMeta) – Projections metadata.

Return type:

None

_get_kernels()[source]#

Obtains required kernels for smoothing

__call__(object)[source]#

Alternative way to call

forward(object)[source]#

Applies the Gaussian smoothing

Parameters:

object (torch.tensor) – Object to smooth

Returns:

Smoothed object

Return type:

torch.tensor

backward(object, norm_constant=None)[source]#

Applies Gaussian smoothing in back projection. Because the operation is symmetric, it is the same as the forward projection.

Parameters:
  • object (torch.tensor) – Object to smooth

  • norm_constant (torch.tensor, optional) – Normalization constant used in iterative algorithms. Defaults to None.

Returns:

Smoothed object

Return type:

torch.tensor