GPU accelerated image processing for everyone
Computes a binary image with pixel values 0 and 1.
All pixel values x of a given input image with value larger or equal to a given threshold t will be set to 1.
f(x,t) = (1 if (x >= t); (0 otherwise))
This plugin is comparable to setting a raw threshold in ImageJ and using the ‘Convert to Mask’ menu.
Categories: Segmentation, Binary
Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clij2_-2.5.0.1.jar.
Ext.CLIJ2_threshold(Image source, Image destination, Number threshold);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer source = clij2.push(sourceImagePlus); destination = clij2.create(source); float threshold = 1.0;
// Execute operation on GPU clij2.threshold(source, destination, threshold);
// show result destinationImagePlus = clij2.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clij2.release(source); clij2.release(destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters source = clij2.pushMat(source_matrix); destination = clij2.create(source); threshold = 1.0;
% Execute operation on GPU clij2.threshold(source, destination, threshold);
% show result destination = clij2.pullMat(destination) % cleanup memory on GPU clij2.release(source); clij2.release(destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters source_sequence = getSequence(); source = clij2.pushSequence(source_sequence); destination = clij2.create(source); threshold = 1.0;
// Execute operation on GPU clij2.threshold(source, destination, threshold);
// show result destination_sequence = clij2.pullSequence(destination) Icy.addSequence(destination_sequence); // cleanup memory on GPU clij2.release(source); clij2.release(destination);
basic_image_processing
binary_processing
count_overlap_between_channels
custom_clij_macro_functions
image_types
labelmap_voronoi
mean_of_touching_neighbors
measure_statistics
morpholibj_classic_watershed
outlines_numbers_overlay
tables
tribolium_morphometry
voronoi
voronoi_otsu_labeling
working_with_rois
count_blobs.ipynb
quantitative_neighbor_maps.ipynb
segmentation_2d_membranes.ipynb
voronoi_otsu_labeling.ipynb
parametric_maps.ipynb
threshold_otsu.ipynb
autoThreshold.ijm
basic_image_processing.ijm
benchmarkVoronoi.ijm
binary_processing.ijm
count_overlap_between_channels.ijm
create_object_outlines.ijm
custom_clij_macro_functions.ijm
distanceMap.ijm
distance_map.ijm
division_visualisation.ijm
getBoundingBox.ijm
image_types.ijm
jaccard_matrix.ijm
labelmap_voronoi.ijm
mean_of_touching_neighbors.ijm
measure_statistics.ijm
morpholibj_classic_watershed.ijm
motionCorrection.ijm
motionCorrection_compare_stackreg.ijm
outlines_numbers_overlay.ijm
tables.ijm
thresholding.ijm
tribolium_morphometry.ijm
voronoi.ijm
voronoi_otsu_labeling.ijm
working_with_rois.ijm
simplePipeline.m
automaticThreshold.js
automaticThreshold.groovy
automaticThreshold.bsh
binaryProcessing.py
count_blobs.py
napari_.py
napari_magicgui.py