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GPU-accelerated image processing in ImageJ using CLIJ

View the Project on GitHub clij/clij-benchmarking

List of benchmarked operations

This list shows benchmarked operations and short Java code visualising how the operations were called. The full implementation of individual operation calls can be found in the respective Java classes: https://github.com/clij/clij-benchmarking-jmh/tree/master/src/main/java/net/haesleinhuepf/clij/benchmark/jmh

Operation ImageJ CLIJ
AddImagesWeighted2D 
ImageCalculator ic = new ImageCalculator();
output = ic.run("Add create", input1, input2);

clij.op().addImagesWeighted(input1, input2, 
    output, 1f, 1f);
AddImagesWeighted3D 
ImageCalculator ic = new ImageCalculator();
output = ic.run("Add create stack", input1, 
    input2);

clij.op().addImagesWeighted(input1, input2, 
    output, 1f, 1f);
AddScalar2D 
IJ.run(input, "Add...", "value=1");

clij.op().addImageAndScalar(input, output, 
    1f);
AddScalar3D 
IJ.run(input, "Add...", "value=1 stack");

clij.op().addImageAndScalar(input, output, 
    1f);
AutoThreshold2D 
IJ.setAutoThreshold(input, "Default dark");
IJ.run(input, "Convert to Mask", 
    "method=Default background=Dark black");    

clij.op().automaticThreshold(input, output, 
    "Default");
AutoThreshold3D 
IJ.setAutoThreshold(input, "Default dark");
IJ.run(input, "Convert to Mask", 
    "method=Default background=Dark black");    

clij.op().automaticThreshold(input, output, 
    "Default");
BinaryAnd2D 
ImageCalculator ic = new ImageCalculator();
output = ic.run("AND create", input1, input2);

clij.op().binaryAnd(input1, input2, output);
BinaryAnd3D 
ImageCalculator ic = new ImageCalculator();
output = ic.run("AND create stack", input1, 
    input2);

clij.op().binaryAnd(input1, input2, output);
Erode2D 
IJ.run(input, "Erode", "");

clij.op().erodeSphere(input, output);
Erode3D 
import process3d.Erode_;
output = new Erode_().erode(input, 1, true);

clij.op().erodeSphere(input, output);
FixedThreshold2D 
IJ.setThreshold(input, 128, 255);
IJ.run(input, "Convert to Mask", 
    "method=Default background=Dark black");

clij.op().threshold(input, output, 128f);
FixedThreshold3D 
IJ.setThreshold(input, 128, 255);
IJ.run(input, "Convert to Mask", 
    "method=Default background=Dark black");

clij.op().threshold(input, output, 128f);
Flip2D 
IJ.run(input, "Flip Horizontally", "");

clij.op().flip(input, output, true, false);
Flip3D 
IJ.run(input, "Flip Horizontally", "stack"); 

clij.op().flip(input, output, true, false, 
    false);
GaussianBlur2D 
IJ.run(input, "Gaussian Blur...", "sigma=" + 
    sigma);

clij.op().blur(input, output, sigma, sigma);
GaussianBlur3D 
IJ.run(input, "Gaussian Blur 3D...", "x=" + 
    sigma + " y=" + sigma + " z=" + sigma);

clij.op().blur(input, output, sigma, sigma, 
    sigma);
MaximumZProjection 
IJ.run(input, "Z Project...", 
    "projection=[Max Intensity]");

clij.op().maximumZProjection(input, output);
Mean2D 
IJ.run(input, "Mean...", "radius=" + radius);

kernelSize = CLIJUtilities.radiusToKernelSize(
    radius);
clij.op().meanSphere(input, output, kernelSize,
    kernelSize);
Mean3D 
IJ.run(input, "Mean 3D...", "x=" + radius + 
    " y=" + radius + " z=" + radius);

kernelSize = CLIJUtilities.radiusToKernelSize(
    radius);
clij.op().meanSphere(input, output, kernelSize,
    kernelSize, kernelSize);
Median2D 
IJ.run(input, "Median...", "radius=" + radius);

kernelSize = CLIJUtilities.radiusToKernelSize(
    radius);
clij.op().medianSphere(input, output, 
    kernelSize, kernelSize);
Median3D 
IJ.run(input, "Median 3D...", "x=" + radius + 
    " y=" + radius + " z=" + radius);

kernelSize = CLIJUtilities.radiusToKernelSize(
    radius);
clij.op().medianSphere(input, output, 
    kernelSize, kernelSize, kernelSize);
Minimum2D 
IJ.run(input, "Minimum...", "radius=" + radius);  

kernelSize = CLIJUtilities.radiusToKernelSize(
    radius);
clij.op().minimumSphere(input, output, 
    kernelSize, kernelSize);
Minimum3D 
IJ.run(input, "Minimum 3D...", "x=" + radius + 
    " y=" + radius + " z=" + radius);

kernelSize = CLIJUtilities.radiusToKernelSize(
    radius);
clij.op().minimumSphere(input, output, 
    kernelSize, kernelSize, kernelSize);
MultiplyScalar2D 
IJ.run(input, "Multiply...", "value=2");

clij.op().multiplyImageAndScalar(input, 
    output, 2f);
MultiplyScalar3D 
IJ.run(input, "Multiply...", "value=2 stack");

clij.op().multiplyImageAndScalar(input, output,
    2f);
RadialReslice 
input.setRoi(new Line(input.getWidth() / 2, 
    input.getWidth() / 2, 0, 0));
Radial_Reslice_Copy rr = 
    new Radial_Reslice_Copy();
rr.setup("", input);
rr.run(input.getProcessor());

numberOfAngles = 360;
angleStepSize = 1.0f;
effectiveNumberOfAngles = (int)((float)
    numberOfAngles / angleStepSize);
maximumRadius = (int)Math.sqrt(
    Math.pow(input.getWidth() / 2, 2) + 
    Math.pow(input.getHeight() / 2, 2));
ClearCLBuffer output =  clij.createCLBuffer(
    new long[]{maximumRadius, 
    input.getDepth(), 
    effectiveNumberOfAngles}, 
    input.getNativeType());
clij.op().radialProjection(input, output, 
    angleStepSize);
Rotate2D 
IJ.run(input, "Rotate 90 Degrees Left", "");

clij.op().rotateLeft(input, output);
Rotate3D 
IJ.run(input, "Rotate 90 Degrees Left", "");   

clij.op().rotateLeft(input, output);

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