Example: Gradient Magnitude

For a scalar image I on a regular grid, RITK estimates physical derivatives with central differences and reports

|grad I| = sqrt((dI/dz)^2 + (dI/dy)^2 + (dI/dx)^2).

Spacing is part of the calculation. A two-voxel intensity change represents a different physical slope when the voxel spacing changes.

let gradient = GradientMagnitudeFilter::new(*input.spacing())
    .apply_native(&input)?;

GradientMagnitudeFilter::unit() is useful only when the image has unit spacing. For physical measurements, pass the image spacing explicitly. The native implementation uses a zero-flux boundary stencil and preserves the input geometry.

Source and verification

Source: crates/ritk-filter/examples/book_processing_pipeline.rs

cargo run -p ritk-filter --example book_processing_pipeline -- \
  docs/book/figures/processing_pipeline.svg

The figure uses one data-derived upper bound for the gradient panel and prints that bound below the image. This prevents a gradient map from looking identical to the input merely because both were independently normalized. Filter tests cover constant fields, linear fields with known spacing, boundary behavior, and native/generic parity.