darsia.TranslationEstimator#

class TranslationEstimator(max_features=200, tol=0.05, keep_percent=0.1)[source]#

Estimator of translation to align images based on feature detection.

Estimation is performed by restriction to ROIs.

Setup of user-defined tuning parameters.

Parameters:

max_featuresint: Feature detection parameter.
tolfloat: Tolerance used to detect whether matching transformation is a translation.

Methods

`find_effective_translation`(img_src, img_dst)	Find a translation aligning two images through feature matching.
`match_roi`(img_src, img_dst[, roi_src, ...])	Align two images through feature matching in provided ROIs.

find_effective_translation(img_src, img_dst, roi_src=None, roi_dst=None, mask_src=None, mask_dst=None, plot_matches=False)[source]#

Find a translation aligning two images through feature matching.

All lengths are in pixels.

Parameters:

img_src, img_dstnumpy.ndarray: Source and destination images.
roi_src, roi_dsttuple of slices, optional: Regions of interest in the source and destination images.
mask_src, mask_dstnumpy.ndarray, optional: Boolean masks of the pixels considered; None means all pixels.
plot_matchesbool, optional: Plot the matched features (debugging). Default False.

Returns:

matrixnumpy.ndarray: Transformation matrix on pixel coordinates (reverse matrix indexing).
successbool: Whether the procedure succeeded.

match_roi(img_src, img_dst, roi_src=None, roi_dst=None, plot_matches=False)[source]#

Align two images through feature matching in provided ROIs.

Parameters:

img_srcnp.ndarray or darsia.Image: Source image.
img_dstnp.ndarray or darsia.Image: Destination image.
roi_srctuple of slices: Region of interested associated to the source image.
roi_dsttuple of slices: Region of interested associated to the destination image translation.
plot_matchesbool: Flag controlling whether the matching features are plotted; useful for debugging; default value is False.

Returns: