Module iaf.reg

Registration functions.

Functions

def apply_rigid_transform(A: numpy.ndarray, R: numpy.ndarray, t: numpy.ndarray)

Applies rotation and translation to coordinates A.

Parameters

A : np.ndarray

Array of 2D or 3D source coordinates with shape [2xN] or [3xN]

R : np.ndarray

Rotation matrix (2x2 or 3x3).

t : np.ndarray

Translation vector (2x1 or 3x1)

Returns

A_t : np.ndarray

Array of 2D or 3D coordinates (shape [2xN] or [3xN]) transformed by rotation matrix R and translation vector t.

def find_rigid_transform(A: numpy.ndarray, B: numpy.ndarray, force_reflection: bool = False)

Calculate rigid transformation to map coordinates A onto coordinates B.

Parameters

A : np.ndarray

Array of 2D or 3D source coordinates with shape [2xN] or [3xN]

B : np.ndarray

Array of 2D or 3D target coordinates A with shape [2xN] or [3xN]

force_reflection : bool

Whether to force reflection if one is suspected: it can give false positives (optional, default False).

Returns

R : np.ndarray

Rotation matrix (either 2x2 or 3x3) to transform the A coordinates into B.

t : np.ndarray

Translation vector (either 2x1 or 3x1) to transform the A coordinates into B.

def multi_image_alignment(images: list[numpy.ndarray], return_composites: bool = False) ‑> Union[tuple[list[numpy.ndarray], numpy.ndarray, numpy.ndarray], list[numpy.ndarray]]

Registers (aligns) a series of images (translation only).

Parameters

images : list[np.ndarray]

List of 2D images to register. The first one will be used as template against which all others will be registered.

return_composites : bool = False

If True, returns two composites of the channels before and after alignment for quality control.

Returns

images : list[np.ndarray]

List of registered images.

rgb_before : np.ndarray

Composite of the channels before alignment.

rgb_after : np.ndarray

Composite of the channels after alignment.