Skip to content
Switch branches/tags
Go to file

Latest commit


Git stats


Failed to load latest commit information.
Latest commit message
Commit time

Join the chat at

ImageJ Ops

ImageJ Ops is an extensible Java framework for algorithms, particularly image processing algorithms. Ops seeks to be a unifying library for scientific image processing. See the Motivation page for details.

Getting started

Each op has a list of typed input and output parameters on which it operates. You can think of an op as a (potentially multi-variable) function:

sum = math.add(a, b)
(phase, amplitude) = fft(image)

In many cases you can also pass a pre-allocated output which will be populated:

math.add(sum, a, b)

Some ops take other ops as inputs, which allows for things like "execute this op on every pixel of that image":

add_op = op("math.add", 5)
output_image = map(input_image, add_op)

For more details, see the "Introduction to ImageJ Ops" tutorial notebook:

Working example

Try this Jython script in ImageJ's Script Editor!

# @ImageJ ij

# create a new blank image
from jarray import array
dims = array([150, 100], 'l')
blank = ij.op().create().img(dims)

# fill in the image with a sinusoid using a formula
formula = "10 * (Math.cos(0.3*p[0]) + Math.sin(0.3*p[1]))"
sinusoid = ij.op().image().equation(blank, formula)

# add a constant value to an image
ij.op().math().add(sinusoid, 13.0)

# generate a gradient image using a formula
gradient = ij.op().image().equation(ij.op().create().img(dims), "p[0]+p[1]")

# add the two images
composite = ij.op().create().img(dims)
ij.op().math().add(composite, sinusoid, gradient)

# display the images
ij.ui().show("sinusoid", sinusoid)
ij.ui().show("gradient", gradient)
ij.ui().show("composite", composite)

The output:

sinusoid gradient composite

How to contribute

We welcome pull requests!


ImageJ Ops: "Write once, run anywhere" image processing




No packages published