Source code for mantidimaging.core.operations.remove_stripe_filtering.remove_stripe_filtering

# Copyright (C) 2023 ISIS Rutherford Appleton Laboratory UKRI
# SPDX - License - Identifier: GPL-3.0-or-later
from __future__ import annotations

from functools import partial
from typing import Dict, Any, TYPE_CHECKING

from algotom.prep.removal import remove_stripe_based_filtering, remove_stripe_based_2d_filtering_sorting

from mantidimaging.core.operations.base_filter import BaseFilter, FilterGroup
from mantidimaging.core.parallel import shared as ps
from mantidimaging.gui.utility.qt_helpers import Type

if TYPE_CHECKING:
    from numpy import ndarray
    from mantidimaging.core.data.imagestack import ImageStack
    from PyQt5.QtWidgets import QSpinBox


[docs]class RemoveStripeFilteringFilter(BaseFilter): """Stripe and ring artifact removal. Combination of algorithm 2 and algorithm 3 in Vo et al., Optics Express 28396 (2018). Removing stripes using the filtering and sorting technique. Source: https://github.com/algotom/algotom Intended to be used on: Sinograms When: If stripes artifacts are present that have not been removed with outliers + flat-fielding the projections Caution: Horizontal stripes caused by changes in image intensity (pixel values) should be fixed by ROI Normalisation instead! """ filter_name = "Remove stripes with filtering" link_histograms = True operate_on_sinograms = True
[docs] @classmethod def filter_func(cls, images: ImageStack, sigma=3, size=21, window_dim=1, filtering_dim=1, progress=None): """ :param sigma: The sigma of the Gaussian window used to separate the low-pass and high-pass components of the intensity profile of each column. :param size: The window size of the median filter to remove large stripes. :param window_dim: Whether to perform the median on 1D or 2D view of the data. :param filtering_dim: Whether to use a 1D or 2D low-pass filter. This uses different Sarepy methods. :return: The ImageStack object with the stripes removed using the filtering and sorting technique. """ params = {"sigma": sigma, "size": size, "dim": window_dim} if images.is_sinograms: if filtering_dim == 1: params["sort"] = True compute_func = cls.compute_function_sino else: compute_func = cls.compute_function_2d_sino else: if filtering_dim == 1: params["sort"] = True compute_func = cls.compute_function else: compute_func = cls.compute_function_2d ps.run_compute_func(compute_func, images.num_sinograms, images.shared_array, params, progress) return images
[docs] @staticmethod def compute_function_sino(index: int, array: ndarray, params: Dict[str, Any]): array[index] = remove_stripe_based_filtering(array[index], **params)
[docs] @staticmethod def compute_function(index: int, array: ndarray, params: Dict[str, Any]): array[:, index, :] = remove_stripe_based_filtering(array[:, index, :], **params)
[docs] @staticmethod def compute_function_2d_sino(index: int, array: ndarray, params: Dict[str, Any]): array[index] = remove_stripe_based_2d_filtering_sorting(array[index], **params)
[docs] @staticmethod def compute_function_2d(index: int, array: ndarray, params: Dict[str, Any]): array[:, index, :] = remove_stripe_based_2d_filtering_sorting(array[:, index, :], **params)
[docs] @staticmethod def register_gui(form, on_change, view): from mantidimaging.gui.utility import add_property_to_form label, _ = add_property_to_form(BaseFilter.SINOGRAM_FILTER_INFO, Type.LABEL, form=form, on_change=on_change) _, sigma = add_property_to_form('Sigma', Type.INT, default_value=3, form=form, on_change=on_change, tooltip="Sigma of the Gaussian window used to separate the low-pass and" " high-pass components of the intensity profile of each column.") _, size = add_property_to_form('Stripe kernel', Type.INT, default_value=21, form=form, on_change=on_change, tooltip="Window size of the median filter to remove large stripes.") _, window_dim = add_property_to_form('Dimension of the window', Type.INT, default_value=1, valid_values=(1, 2), form=form, on_change=on_change, tooltip="Whether to perform the median on 1D or 2D view of the data") _, filtering_dim = add_property_to_form('Filtering dim', Type.INT, default_value=1, valid_values=(1, 2), form=form, on_change=on_change, tooltip="Whether to use a 1D or 2D low-pass filter. " "This uses different Sarepy methods") return {'sigma': sigma, 'size': size, 'window_dim': window_dim, 'filtering_dim': filtering_dim}
[docs] @staticmethod def execute_wrapper(sigma: QSpinBox, size: QSpinBox, window_dim: QSpinBox, filtering_dim: QSpinBox): # type: ignore return partial(RemoveStripeFilteringFilter.filter_func, sigma=sigma.value(), size=size.value(), window_dim=window_dim.value(), filtering_dim=filtering_dim.value())
[docs] @staticmethod def group_name() -> FilterGroup: return FilterGroup.Advanced