modeOfNNearestNeighborsMap

Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the mode 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.

Parameters

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 clij2_-2.5.0.1.jar.

Usage in ImageJ macro

Ext.CLIJ2_modeOfNNearestNeighborsMap(Image parametric_map, Image label_map, Image parametric_map_destination, Number n);

Usage in object oriented programming languages

Java

// init CLIJ and GPU
import net.haesleinhuepf.clij2.CLIJ2;
import net.haesleinhuepf.clij.clearcl.ClearCLBuffer;
CLIJ2 clij2 = CLIJ2.getInstance();

// get input parameters
ClearCLBuffer parametric_map = clij2.push(parametric_mapImagePlus);
ClearCLBuffer label_map = clij2.push(label_mapImagePlus);
parametric_map_destination = clij2.create(parametric_map);
int n = 10;

// Execute operation on GPU
clij2.modeOfNNearestNeighborsMap(parametric_map, label_map, parametric_map_destination, n);

// show result
parametric_map_destinationImagePlus = clij2.pull(parametric_map_destination);
parametric_map_destinationImagePlus.show();

// cleanup memory on GPU
clij2.release(parametric_map);
clij2.release(label_map);
clij2.release(parametric_map_destination);

Matlab

% init CLIJ and GPU
clij2 = init_clatlab();

% get input parameters
parametric_map = clij2.pushMat(parametric_map_matrix);
label_map = clij2.pushMat(label_map_matrix);
parametric_map_destination = clij2.create(parametric_map);
n = 10;

% Execute operation on GPU
clij2.modeOfNNearestNeighborsMap(parametric_map, label_map, parametric_map_destination, n);

% show result
parametric_map_destination = clij2.pullMat(parametric_map_destination)

% cleanup memory on GPU
clij2.release(parametric_map);
clij2.release(label_map);
clij2.release(parametric_map_destination);

Icy JavaScript

// init CLIJ and GPU
importClass(net.haesleinhuepf.clicy.CLICY);
importClass(Packages.icy.main.Icy);

clij2 = CLICY.getInstance();

// get input parameters
parametric_map_sequence = getSequence();
parametric_map = clij2.pushSequence(parametric_map_sequence);
label_map_sequence = getSequence();
label_map = clij2.pushSequence(label_map_sequence);
parametric_map_destination = clij2.create(parametric_map);
n = 10;

// Execute operation on GPU
clij2.modeOfNNearestNeighborsMap(parametric_map, label_map, parametric_map_destination, n);

// show result
parametric_map_destination_sequence = clij2.pullSequence(parametric_map_destination)
Icy.addSequence(parametric_map_destination_sequence);
// cleanup memory on GPU
clij2.release(parametric_map);
clij2.release(label_map);
clij2.release(parametric_map_destination);

clEsperanto Python (experimental)

import pyclesperanto_prototype as cle

cle.mode_of_n_nearest_neighbors_map(parametric_map, label_map, parametric_map_destination, n)

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