ph_perona_malik — 2D physics op

• Data kinds: image → image

• Call: fullseye.apply(img, "ph_perona_malik", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Perona-Malik anisotropic diffusion (HALCON `anisotropic_diffusion`).

Explicit update I <- I + lam * sum_dir g(|grad_dir|) * grad_dir with the

Perona-Malik conductance `g(s) = 1/(1+(s/k)^2)`: on a strong edge (|grad|>>k)

g->0 so the edge is preserved, while inside a flat noisy region (|grad|<<k)

g->1 so it diffuses like the heat equation. `a` sets the number of steps,

`b the edge threshold k`.

Detailed usage guide

• gallery2d_physics_alife_3d family guide

References (sample data, literature)

• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).

• Operator provenance and references — the sources of the research/methods this op family came from.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (physics)

ph_coherence_enhancing_diffusion · ph_reaction_diffusion · ph_heat_flow · ph_mean_curvature_motion · ph_total_variation_flow

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.