GPU accelerated image processing for everyone
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the standard deviation value of neighboring labels. The distance number of nearest neighbors can be configured. Note: Values of all pixels in a label each must be identical.
parametric_map : Image label_map : Image parametric_map_destination : Image n : int number of nearest neighbors
Categories: Measurements, Filter, Graphs
Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clijx_-0.30.1.21.jar.
Ext.CLIJx_standardDeviationOfNNearestNeighborsMap(Image parametric_map, Image label_map, Image parametric_map_destination, Number n);
// init CLIJ and GPU import net.haesleinhuepf.clijx.CLIJx; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJx clijx = CLIJx.getInstance(); // get input parameters ClearCLBuffer parametric_map = clijx.push(parametric_mapImagePlus); ClearCLBuffer label_map = clijx.push(label_mapImagePlus); parametric_map_destination = clijx.create(parametric_map); int n = 10;
// Execute operation on GPU clijx.standardDeviationOfNNearestNeighborsMap(parametric_map, label_map, parametric_map_destination, n);
// show result parametric_map_destinationImagePlus = clijx.pull(parametric_map_destination); parametric_map_destinationImagePlus.show(); // cleanup memory on GPU clijx.release(parametric_map); clijx.release(label_map); clijx.release(parametric_map_destination);
% init CLIJ and GPU clijx = init_clatlabx(); % get input parameters parametric_map = clijx.pushMat(parametric_map_matrix); label_map = clijx.pushMat(label_map_matrix); parametric_map_destination = clijx.create(parametric_map); n = 10;
% Execute operation on GPU clijx.standardDeviationOfNNearestNeighborsMap(parametric_map, label_map, parametric_map_destination, n);
% show result parametric_map_destination = clijx.pullMat(parametric_map_destination) % cleanup memory on GPU clijx.release(parametric_map); clijx.release(label_map); clijx.release(parametric_map_destination);
import pyclesperanto_prototype as cle cle.standard_deviation_of_n_nearest_neighbors_map(parametric_map, label_map, parametric_map_destination, n)