ScaleView Op¶

In [1]:

//load ImageJ
%classpath config resolver scijava.public https://maven.scijava.org/content/groups/public
%classpath add mvn net.imagej imagej 2.0.0-rc-67

//create ImageJ object
ij = new net.imagej.ImageJ()

Added new repo: scijava.public

Out[1]:

net.imagej.ImageJ@465e45d7

This Op wraps the Views.scale() method of ImgLib2, enlarging the image by a set of scale factors. Let's see how the Op is called: through the use of an interpolator and an OutOfBoundsFactory.

In [2]:

ij.op().help('scaleView')

Out[2]:

Available operations:
	(RandomAccessibleInterval out) =
	net.imagej.ops.transform.scaleView.DefaultScaleView(
		RandomAccessibleInterval in,
		double[] scaleFactors,
		InterpolatorFactory interpolator,
		OutOfBoundsFactory outOfBoundsFactory?)

Note that the Op takes the following parameters:

RandomAccessibleInterval in: the input image
double[] scaleFactors: an array an element for each dimension that describes the factor to which that dimension is to be increased by (i.e. a value of 2 implies that the corresponding dimension should be twice as large in the output)
InterpolatorFactory interpolator: this Object tells the Op how to interpolate the spaces in between the known data points. There are many different types of interpolation that are supported by ImageJ.
OutOfBoundsFactory outOfBoundsFactory: an optonal parameter that tells the Op how to handle cases close to the edge of the image. Since this parameter is optional we won't worry about it here.

Let's find a really small image to scale up:

In [3]:

input = ij.scifio().datasetIO().open("http://imagej.net/images/ij-icon.gif")

ij.notebook().display(input)

[INFO] Verifying GIF format
[INFO] Reading dimensions
[INFO] Reading data blocks

Out[3]:

First, let's try scaling it using nearest neighbor interpolation:

In [4]:

import net.imglib2.interpolation.randomaccess.NearestNeighborInterpolatorFactory

scaleFactors = [4, 4, 1] // Enlarge X and Y by 4x; leave channel count the same.

scaled = ij.op().run("scaleView", input, scaleFactors, new NearestNeighborInterpolatorFactory())

ij.notebook().display(scaled)

Out[4]:

Nice and pixel-y. If we want something smoother, we can try N-Linear interpolation:

In [5]:

import net.imglib2.interpolation.randomaccess.LanczosInterpolatorFactory

scaleFactors = [4, 4, 1] // Enlarge X and Y by 4x; leave channel count the same.

input = ij.scifio().datasetIO().open("http://imagej.net/images/ij-icon.gif")

scaled = ij.op().run("scaleView", input, scaleFactors, new LanczosInterpolatorFactory())

ij.notebook().display(scaled)

[INFO] Verifying GIF format
[INFO] Reading dimensions
[INFO] Reading data blocks

Out[5]:

Be sure to take a look at interpolateView, as it is somewhat related to our scaleView Op.