mcc_scoring#

mcc_scoring(template, template_mask, template_filter, ft_target, ft_target2, ft_target_mask, fast_shape, fast_ft_shape, rotations, callback, interpolation_order, overlap_ratio=0.3)[source]#

Computes a normalized cross-correlation score between target (f), template (g), template_mask (m) and target_mask (t)

$$\frac{CC(f,g)-\frac{CC(f,m)\cdot CC(t,g)}{CC(t,m)}}{\sqrt{(CC(f^2,m)-\frac{CC(f,m{)}^2}{CC(t,m)})\cdot (CC(t,g^2)-\frac{CC(t,g{)}^2}{CC(t,m)})}},$$

where

$$CC(f,g)={\mathcal{F}}^{-1}(\mathcal{F}(f)\cdot \mathcal{F}(g{)}^{\ast }).$$

Parameters:

templateUnion[Tuple[type, tuple of ints, type], BackendArray]

Template data buffer, its shape and datatype.

template_maskUnion[Tuple[type, tuple of ints, type], BackendArray]

Template mask data buffer, its shape and datatype.

template_filterUnion[Tuple[type, tuple of ints, type], BackendArray]

Template filter data buffer, its shape and datatype.

ft_targetUnion[Tuple[type, tuple of ints, type], BackendArray]

Fourier transformed target data buffer, its shape and datatype.

ft_target2Union[Tuple[type, tuple of ints, type], BackendArray]

Fourier transformed squared target data buffer, its shape and datatype.

ft_target_maskUnion[Tuple[type, tuple of ints, type], BackendArray]

Fourier transformed target mask data buffer, its shape and datatype.

fast_shape: tuple of ints

Data shape for the forward Fourier transform.

fast_ft_shape: tuple of ints

Data shape for the inverse Fourier transform.

rotationsBackendArray

Rotation matrices to be sampled (n, d, d).

callbackCallbackClass

A callable for processing the result of each rotation.

interpolation_orderint

Spline order for template rotations.

overlap_ratiofloat, optional

Required fractional mask overlap, 0.3 by default.

References

[1]

Masked FFT registration, Dirk Padfield, CVPR 2010 conference

[2]

https://scikit-image.org/docs/stable/api/skimage.registration.html