Examples with FinalInterval net.imglib2.FinalInterval used on opensource projects

Example 31 with FinalInterval

use of net.imglib2.FinalInterval in project imagej-ops by imagej.

the class ListDilate method compute.

@Override
public void compute(final RandomAccessibleInterval<T> in1, final List<Shape> in2, final IterableInterval<T> out) {
    final long[][] minSize = Morphologies.computeMinSize(in1, in2);
    final Interval interval = new FinalInterval(minSize[1]);
    Img<T> upstream = imgCreator.calculate(interval);
    Img<T> downstream = imgCreator.calculate(interval);
    Img<T> tmp;
    dilateComputer.compute(in1, in2.get(0), Views.translate(downstream, minSize[0]));
    for (int i = 1; i < in2.size(); i++) {
        // Ping-ponging intermediate results between upstream and downstream to
        // avoid repetitively creating new Imgs.
        tmp = downstream;
        downstream = upstream;
        upstream = tmp;
        dilateComputer.compute(upstream, in2.get(i), downstream);
    }
    if (isFull)
        copyImg.compute(downstream, out);
    else
        copyImg.compute(Views.interval(Views.translate(downstream, minSize[0]), out), out);
}

Example 32 with FinalInterval

use of net.imglib2.FinalInterval in project imagej-ops by imagej.

the class DefaultScaleView method calculate.

@Override
public RandomAccessibleInterval<T> calculate(RandomAccessibleInterval<T> input) {
    final long[] newDims = Intervals.dimensionsAsLongArray(in());
    for (int i = 0; i < Math.min(scaleFactors.length, in().numDimensions()); i++) {
        newDims[i] = Math.round(in().dimension(i) * scaleFactors[i]);
    }
    IntervalView<T> interval = Views.interval(Views.raster(RealViews.affineReal(Views.interpolate(Views.extendMirrorSingle(input), interpolator), new Scale(scaleFactors))), new FinalInterval(newDims));
    return interval;
}

Example 33 with FinalInterval

use of net.imglib2.FinalInterval in project imagej-ops by imagej.

the class PaddingIntervalOrigin method calculate.

@Override
@SuppressWarnings("unchecked")
public O calculate(final I input, final Interval centeredInterval) {
    int numDimensions = input.numDimensions();
    // compute where to place the final Interval for the input so that the
    // coordinate in the center
    // of the input is at position (0,0).
    final long[] min = new long[numDimensions];
    final long[] max = new long[numDimensions];
    for (int d = 0; d < numDimensions; ++d) {
        min[d] = input.min(d) + input.dimension(d) / 2;
        max[d] = min[d] + centeredInterval.dimension(d) - 1;
    }
    return (O) new FinalInterval(min, max);
}

Example 34 with FinalInterval

use of net.imglib2.FinalInterval in project imagej-ops by imagej.

the class DefaultBilateral method compute.

@Override
public void compute(final RandomAccessibleInterval<I> input, final RandomAccessibleInterval<O> output) {
    final long[] size = new long[input.numDimensions()];
    input.dimensions(size);
    final RandomAccess<O> outputRA = output.randomAccess();
    final Cursor<I> inputCursor = Views.iterable(input).localizingCursor();
    final long[] currentPos = new long[input.numDimensions()];
    final long[] neighborhoodPos = new long[input.numDimensions()];
    final long[] neighborhoodMin = new long[input.numDimensions()];
    final long[] neighborhoodMax = new long[input.numDimensions()];
    Neighborhood<I> neighborhood;
    Cursor<I> neighborhoodCursor;
    final RectangleNeighborhoodFactory<I> fac = RectangleNeighborhood.factory();
    while (inputCursor.hasNext()) {
        inputCursor.fwd();
        inputCursor.localize(currentPos);
        double distance;
        inputCursor.localize(neighborhoodMin);
        inputCursor.localize(neighborhoodMax);
        neighborhoodMin[0] = Math.max(0, neighborhoodMin[0] - radius);
        neighborhoodMin[1] = Math.max(0, neighborhoodMin[1] - radius);
        neighborhoodMax[0] = Math.min(input.max(0), neighborhoodMax[0] + radius);
        neighborhoodMax[1] = Math.min(input.max(1), neighborhoodMax[1] + radius);
        final Interval interval = new FinalInterval(neighborhoodMin, neighborhoodMax);
        neighborhood = fac.create(currentPos, neighborhoodMin, neighborhoodMax, interval, input.randomAccess());
        neighborhoodCursor = neighborhood.localizingCursor();
        double weight, v = 0.0;
        double w = 0.0;
        do {
            neighborhoodCursor.fwd();
            neighborhoodCursor.localize(neighborhoodPos);
            distance = getDistance(currentPos, neighborhoodPos);
            // spatial kernel
            weight = gauss(distance, sigmaS);
            // intensity
            distance = Math.abs(inputCursor.get().getRealDouble() - neighborhoodCursor.get().getRealDouble());
            // difference
            // range kernel, then exponent addition
            weight *= gauss(distance, sigmaR);
            v += weight * neighborhoodCursor.get().getRealDouble();
            w += weight;
        } while (neighborhoodCursor.hasNext());
        outputRA.setPosition(currentPos);
        outputRA.get().setReal(v / w);
    }
}

Example 35 with FinalInterval

use of net.imglib2.FinalInterval in project imagej-ops by imagej.

the class DefaultCreateKernel2ndDerivBiGauss method calculate.

@Override
public RandomAccessibleInterval<T> calculate(final double[] sigmas, final Integer dimensionality) {
    // both sigmas must be available
    if (sigmas.length < 2)
        throw new IllegalArgumentException("Two sigmas (for inner and outer Gauss)" + " must be supplied.");
    // both sigmas must be reasonable
    if (sigmas[0] <= 0 || sigmas[1] <= 0)
        throw new IllegalArgumentException("Input sigmas must be both positive.");
    // dimension as well...
    if (dimensionality <= 0)
        throw new IllegalArgumentException("Input dimensionality must both positive.");
    // the size and center of the output image
    final long[] dims = new long[dimensionality];
    final long[] centre = new long[dimensionality];
    // time-saver... (must hold now: dimensionality > 0)
    // NB: size of the image is 2px wider than for 0th order BiGauss to have
    // some space for smooth approach-to-zero at the kernel image borders
    dims[0] = Math.max(3, (2 * (int) (sigmas[0] + 3 * sigmas[1] + 0.5) + 1)) + 2;
    centre[0] = (int) (dims[0] / 2);
    // fill the size and center arrays
    for (int d = 1; d < dims.length; d++) {
        dims[d] = dims[0];
        centre[d] = centre[0];
    }
    // prepare some scaling constants
    /*
		//orig full math version:
		final double k = (sigmas[1]/sigmas[0]) * (sigmas[1]/sigmas[0]); //eq. (6)
		final double[] C = { 1.0/(2.50663*sigmas[0]*sigmas[0]*sigmas[0]), 1.0/(2.50663*sigmas[1]*sigmas[1]*sigmas[1]) };
		//2.50663 = sqrt(2*PI)
		*/
    // less math version:
    // note that originally there was C[0] for inner Gauss, k*C[1] for outer Gauss
    // we get rid of k by using new C[0] and C[1]:
    final double[] C = { 1.0 / (2.50663 * sigmas[0] * sigmas[0] * sigmas[0]), 1.0 / (2.50663 * sigmas[1] * sigmas[0] * sigmas[0]) };
    // prepare squared input sigmas
    final double[] sigmasSq = { sigmas[0] * sigmas[0], sigmas[1] * sigmas[1] };
    // prepare the output image
    final RandomAccessibleInterval<T> out = createImgOp.calculate(new FinalInterval(dims));
    // fill the output image
    final Cursor<T> cursor = Views.iterable(out).cursor();
    while (cursor.hasNext()) {
        cursor.fwd();
        // obtain the current coordinate (use dims to store it)
        cursor.localize(dims);
        // calculate distance from the image centre
        // TODO: can JVM reuse this var or is it allocated again and again (and multipling in the memory)?
        double dist = 0.;
        for (int d = 0; d < dims.length; d++) {
            final double dx = dims[d] - centre[d];
            dist += dx * dx;
        }
        // dist = Math.sqrt(dist); -- gonna work with squared distance
        // which of the two Gaussians should we use?
        double val = 0.;
        if (dist < sigmasSq[0]) {
            // the inner one
            val = (dist / sigmasSq[0]) - 1.0;
            val *= C[0] * Math.exp(-0.5 * dist / sigmasSq[0]);
        } else {
            // the outer one, get new distance first:
            dist = Math.sqrt(dist) - (sigmas[0] - sigmas[1]);
            dist *= dist;
            val = (dist / sigmasSq[1]) - 1.0;
            val *= C[1] * Math.exp(-0.5 * dist / sigmasSq[1]);
        }
        // compose the real value finally
        cursor.get().setReal(val);
    }
    return out;
}