nanopyx.methods.channel_registration

 1from .estimator import ChannelRegistrationEstimator
 2from .corrector import ChannelRegistrationCorrector
 3from ...core.utils.timeit import timeit
 4
 5
 6def estimate_channel_registration(
 7    image_array,
 8    ref_channel,
 9    max_shift,
10    blocks_per_axis,
11    min_similarity,
12    save_translation_masks=True,
13    translation_mask_save_path=None,
14    apply=True,
15):
16    """
17    Function used to estimate shift between different color channels and align them of an image based on cross correlation.
18    :param image_array:numpy array  with shape (n_channels, y, x); image to be corrected
19    :param ref_channel: int; channel index to be used as reference
20    :param max_shift: int; maximum shift accepted for correction, in pixels.
21    :param blocks_per_axis: int; number of blocks to divide the image in both x and y dimensions
22    :param min_similarity: float; minimum value of similarity to accept a shift as a correction
23    subpixel precision, max simply takes the maximum of the cross correlation map
24    :param save_translation_masks: bool, defaults to True; whether to save translation masks as a tif or not
25    :param translation_mask_save_path: str; path where to save translation masks
26    :param apply: bool; whether to apply the correction if True or only estimate if False
27    :return: if apply==True, returns corrected image with shape (c, y, x)
28    """
29    estimator = ChannelRegistrationEstimator()
30    aligned_image = estimator.estimate(
31        image_array,
32        ref_channel,
33        max_shift,
34        blocks_per_axis,
35        min_similarity,
36        save_translation_masks=save_translation_masks,
37        translation_mask_save_path=translation_mask_save_path,
38        apply=apply,
39    )
40
41    if aligned_image is not None:
42        return aligned_image
43    else:
44        pass
45
46
47def apply_channel_registration(image_array, translation_masks=None):
48    """
49    Function used to align different color channels of an image based on cross correlation.
50    :param image_array: numpy array with shape (n_channels, y, x); image to be registered
51    :param translation_masks: numpy array of translation masks
52    :return: returns corrected image with shape (c, y, x)
53    """
54    corrector = ChannelRegistrationCorrector()
55    aligned_image = corrector.align_channels(image_array, translation_masks=translation_masks)
56
57    return aligned_image