GPU accelerated image processing for everyone
By Robert Haase, based on work by Bradley Lowekamp and the SimpleITK and ITK teams
Apply SimpleITKs Wiener Deconvolution to an image.
See also: https://itk.org/Doxygen/html/classitk_1_1WienerDeconvolutionImageFilter.html
Category: Filter
Availability: Available in Fiji by activating the update sites clij, clij2 and clijx-assistant-extensions. This function is part of clijx-assistant-simpleitk_-0.6.0.1.jar.
Ext.CLIJx_simpleITKWienerDeconvolution(Image input, Image input_psf, Image destination, Number noise_variance, Boolean normalize);
// init CLIJ and GPU import net.haesleinhuepf.clijx.CLIJx; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJx clijx = CLIJx.getInstance(); // get input parameters ClearCLBuffer input = clijx.push(inputImagePlus); ClearCLBuffer input_psf = clijx.push(input_psfImagePlus); destination = clijx.create(input); float noise_variance = 1.0; boolean normalize = true;
// Execute operation on GPU clijx.simpleITKWienerDeconvolution(input, input_psf, destination, noise_variance, normalize);
// show result destinationImagePlus = clijx.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clijx.release(input); clijx.release(input_psf); clijx.release(destination);
% init CLIJ and GPU clijx = init_clatlabx(); % get input parameters input = clijx.pushMat(input_matrix); input_psf = clijx.pushMat(input_psf_matrix); destination = clijx.create(input); noise_variance = 1.0; normalize = true;
% Execute operation on GPU clijx.simpleITKWienerDeconvolution(input, input_psf, destination, noise_variance, normalize);
% show result destination = clijx.pullMat(destination) % cleanup memory on GPU clijx.release(input); clijx.release(input_psf); clijx.release(destination);
This plugin is licensed BSD3, see:
https://github.com/clij/clijx-assistant-simpleitk/blob/master/license.txt
The underlying SimpleITK librariy is Apache 2 licensed:
https://github.com/SimpleITK/SimpleITK/blob/master/LICENSE