replaceIntensities

Replaces integer intensities specified in a vector image.

The vector image must be 3D with size (m, 1, 1) where m corresponds to the maximum intensity in the original image. Assuming the vector image contains values (0, 1, 0, 2) means:

All pixels with value 0 (first entry in the vector image) get value 0
All pixels with value 1 get value 1
All pixels with value 2 get value 0
All pixels with value 3 get value 2

Category: Filter

Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clij2_-2.5.0.1.jar.

replaceIntensities often follows after

connectedComponentsLabelingBox (2)
pushResultsTableColumn (2)
labelVoronoiOctagon (8)
medianOfTouchingNeighbors (4)
greaterOrEqualConstant (1)
meanOfTouchingNeighbors (4)
averageDistanceOfTouchingNeighbors (1)
standardDeviationOfTouchingNeighbors (2)
minimumOfTouchingNeighbors (4)
transposeXY (1)
maximum2DBox (2)
greaterConstant (1)
maximumYProjection (1)
maximumOfTouchingNeighbors (4)
addImageAndScalar (1)
smallerConstant (1)
mask (2)

replaceIntensities is often followed by

Usage in ImageJ macro

Ext.CLIJ2_replaceIntensities(Image input, Image new_values_vector, Image destination);

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 input = clij2.push(inputImagePlus);
ClearCLBuffer new_values_vector = clij2.push(new_values_vectorImagePlus);
destination = clij2.create(input);

// Execute operation on GPU
clij2.replaceIntensities(input, new_values_vector, destination);

// show result
destinationImagePlus = clij2.pull(destination);
destinationImagePlus.show();

// cleanup memory on GPU
clij2.release(input);
clij2.release(new_values_vector);
clij2.release(destination);

Matlab

% init CLIJ and GPU
clij2 = init_clatlab();

% get input parameters
input = clij2.pushMat(input_matrix);
new_values_vector = clij2.pushMat(new_values_vector_matrix);
destination = clij2.create(input);

% Execute operation on GPU
clij2.replaceIntensities(input, new_values_vector, destination);

% show result
destination = clij2.pullMat(destination)

% cleanup memory on GPU
clij2.release(input);
clij2.release(new_values_vector);
clij2.release(destination);

Icy JavaScript

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

clij2 = CLICY.getInstance();

// get input parameters
input_sequence = getSequence();
input = clij2.pushSequence(input_sequence);
new_values_vector_sequence = getSequence();
new_values_vector = clij2.pushSequence(new_values_vector_sequence);
destination = clij2.create(input);

// Execute operation on GPU
clij2.replaceIntensities(input, new_values_vector, destination);

// show result
destination_sequence = clij2.pullSequence(destination)
Icy.addSequence(destination_sequence);
// cleanup memory on GPU
clij2.release(input);
clij2.release(new_values_vector);
clij2.release(destination);

clEsperanto Python (experimental)

import pyclesperanto_prototype as cle

cle.replace_intensities(input, new_values_vector, destination)

Example notebooks

filtering_in_graphs
mean_of_touching_neighbors
neighbors_of_neighbors
parametric_images
superpixel_segmentation
tribolium_morphometry
mesh_between_touching_neighbors.ipynb
neighborhood_definitions.ipynb
neighbors_of_neighbors.ipynb
bead_segmentation.ipynb
tissue_neighborhood_quantification.ipynb

Example scripts

division_visualisation.ijm
filtering_in_graphs.ijm
jaccard_matrix.ijm
mean_of_touching_neighbors.ijm
neighbors_of_neighbors.ijm
parametric_images.ijm
superpixel_segmentation.ijm
tribolium_morphometry.ijm

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