Package net.imglib2.interpolation.randomaccess

Class NLinearInterpolator3D<T extends NumericType<T>>

java.lang.Object
net.imglib2.AbstractEuclideanSpace
net.imglib2.position.transform.AbstractPositionableTransform<RandomAccess<T>>
net.imglib2.position.transform.Floor<RandomAccess<T>>
net.imglib2.interpolation.randomaccess.NLinearInterpolator<T>
net.imglib2.interpolation.randomaccess.NLinearInterpolator3D<T>
Type Parameters:
T -
All Implemented Interfaces:
EuclideanSpace, Positionable, RealLocalizable, RealPositionable, RealRandomAccess<T>, Sampler<T>
public class NLinearInterpolator3D<T extends NumericType<T>> extends NLinearInterpolator<T>
Author:
Stephan Preibisch, Stephan Saalfeld, Tobias Pietzsch

  • Constructor Details

    • NLinearInterpolator3D

      protected NLinearInterpolator3D(NLinearInterpolator3D<T> interpolator)

    • NLinearInterpolator3D

      protected NLinearInterpolator3D(RandomAccessible<T> randomAccessible, T type)

    • NLinearInterpolator3D

      protected NLinearInterpolator3D(RandomAccessible<T> randomAccessible)

  • Method Details

    • numDimensions

      public final int numDimensions()
      Description copied from interface: EuclideanSpace
      Gets the space's number of dimensions.
      Specified by:
      numDimensions in interface EuclideanSpace
      Overrides:
      numDimensions in class AbstractEuclideanSpace

    • fillWeights

      protected void fillWeights()
      Description copied from class: NLinearInterpolator
      Fill the NLinearInterpolator.weights array.

      Let w_d denote the fraction of a pixel at which the sample position p_d lies from the floored position pf_d in dimension d. That is, the value at pf_d contributes with (1 - w_d) to the sampled value; the value at ( pf_d + 1 ) contributes with w_d.

      At every pixel, the total weight results from multiplying the weights of all dimensions for that pixel. That is, the "top-left" contributing pixel (position floored in all dimensions) gets assigned weight (1-w_0)(1-w_1)...(1-w_n).

      We work through the weights array starting from the highest dimension. For the highest dimension, the first half of the weights contain the factor (1 - w_n) because this first half corresponds to floored pixel positions in the highest dimension. The second half contain the factor w_n. In this first step, the first weight of the first half gets assigned (1 - w_n). The first element of the second half gets assigned w_n

      From their, we work recursively down to dimension 0. That is, each half of weights is again split recursively into two partitions. The first element of the second partitions is the first element of the half multiplied with (w_d). The first element of the first partitions is multiplied with (1 - w_d).

      When we have reached dimension 0, all weights will have a value assigned.

      Overrides:
      fillWeights in class NLinearInterpolator<T extends NumericType<T>>

    • get

      public T get()
      Description copied from class: NLinearInterpolator
      Get the interpolated value at the current position.

      To visit the pixels that contribute to an interpolated value, we move in a (binary-reflected) Gray code pattern, such that only one dimension of the target position is modified per move.

      See http://en.wikipedia.org/ wiki/Gray_code

      Specified by:
      get in interface Sampler<T extends NumericType<T>>
      Overrides:
      get in class NLinearInterpolator<T extends NumericType<T>>

    • copy

      public NLinearInterpolator3D<T> copy()
      Specified by:
      copy in interface Sampler<T extends NumericType<T>>
      Overrides:
      copy in class NLinearInterpolator<T extends NumericType<T>>
      Returns:
      - A new Sampler in the same state accessing the same values. It does NOT copy T, just the state of the Sampler. Otherwise use T.copy() if available. Sampler.copy().get() == Sampler.get(), i.e. both hold the same value, not necessarily the same instance (this is the case for an ArrayCursor for example)