# Copyright 2014 Diamond Light Source Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
.. module:: ring_removal_fitting
:platform: Unix
:synopsis: Method working in the sinogram space to remove ring artifacts.
.. moduleauthor:: Nghia Vo <scientificsoftware@diamond.ac.uk>
"""
from savu.plugins.plugin import Plugin
from savu.plugins.driver.cpu_plugin import CpuPlugin
from savu.plugins.utils import register_plugin
import numpy as np
import pyfftw.interfaces.scipy_fftpack as fft
from scipy.signal import savgol_filter
[docs]@register_plugin
class RingRemovalFitting(Plugin, CpuPlugin):
def __init__(self):
super(RingRemovalFitting, self).__init__(
"RingRemovalFitting")
[docs] def setup(self):
in_dataset, out_dataset = self.get_datasets()
out_dataset[0].create_dataset(in_dataset[0])
in_pData, out_pData = self.get_plugin_datasets()
in_pData[0].plugin_data_setup('SINOGRAM', 'single')
out_pData[0].plugin_data_setup('SINOGRAM', 'single')
def _create_2d_window(self, height, width, sigmax, sigmay):
"""Create a 2D Gaussian window.
Parameters
-----------
height, width : shape of the window.
sigmax, sigmay : sigmas of the window.
Returns
---------
2D array.
"""
centerx = (width - 1.0) / 2.0
centery = (height - 1.0) / 2.0
y, x = np.ogrid[-centery:height - centery, -centerx:width - centerx]
numx = 2.0 * sigmax * sigmax
numy = 2.0 * sigmay * sigmay
win2d = np.exp(-(x * x / numx + y * y / numy))
return win2d
[docs] def pre_process(self):
in_pData = self.get_plugin_in_datasets()
width_dim = \
in_pData[0].get_data_dimension_by_axis_label('detector_x')
height_dim = \
in_pData[0].get_data_dimension_by_axis_label('rotation_angle')
sino_shape = list(in_pData[0].get_shape())
self.pad = min(int(0.1 * sino_shape[height_dim]), 50)
self.width1 = sino_shape[width_dim] + 2 * self.pad
self.height1 = sino_shape[height_dim] + 2 * self.pad
sigmax = np.clip(np.int16(
self.parameters['sigmax']), 1, self.width1 - 1)
sigmay = np.clip(np.int16(
self.parameters['sigmay']), 1, self.height1 - 1)
self.window2d = self._create_2d_window(
self.height1, self.width1, sigmax, sigmay)
self.order = np.clip(
np.int16(self.parameters['order']), 0, self.height1 - 1)
listx = np.arange(0, self.width1)
listy = np.arange(0, self.height1)
x, y = np.meshgrid(listx, listy)
self.matsign = np.power(-1.0, x + y)
[docs] def process_frames(self, data):
sinogram = data[0]
(height, _) = sinogram.shape
if height % 2 == 0:
height = height - 1
sinofit = np.abs(savgol_filter(
sinogram, height, self.order, axis=0, mode='mirror'))
sinofit2 = np.pad(
sinofit, ((0, 0), (self.pad, self.pad)), mode='edge')
sinofit2 = np.pad(
sinofit2, ((self.pad, self.pad), (0, 0)), mode='mean')
sinofitsmooth = np.real(fft.ifft2(fft.fft2(
sinofit2 * self.matsign) * self.window2d) * self.matsign)
sinofitsmooth = sinofitsmooth[self.pad:self.height1 - self.pad,
self.pad:self.width1 - self.pad]
num1 = np.mean(sinofit)
num2 = np.mean(sinofitsmooth)
sinofitsmooth = num1 * sinofitsmooth / num2
return sinogram / sinofit * sinofitsmooth