xsitk_curv_aniso_diff — 2D extra op

Data kinds: imageimage

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

xsitk_curv_aniso_diff: 入力 → 出力

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*

Usage

Curvature anisotropic diffusion (SimpleITK `CurvatureAnisotropicDiffusion`). A type of Perona-Malik-style anisotropic diffusion that suppresses diffusion at edges (locations with large gradients) and diffuses freely in flat areas, smoothing while preserving edges.

> The detailed description below is the original text — the summary and the headings are translated.

`a は伝導度パラメータ(conductance、0.5+4.5*a で 0.5〜5.0。大きいほどエッジ判定が緩くなり強く拡散する)、b` は反復回数(1〜9 回)を振る。時間刻みは 0.0625 固定。出力は [0,1] にクリップ。

Detailed usage guide

gallery2d_color_artistic 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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

xsitk_curv_aniso_diff 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

gallery2d_color_artisticpy -3.11 examples/gallery2d_color_artistic.py

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

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

Same category (extra)

xsitk_curvature_flow · xsitk_minmax_curv_flow · xsitk_laplacian_sharpen · xsitk_grayscale_fillhole · xsitk_grayscale_grindpeak · xsitk_opening_by_recon · xsitk_closing_by_recon · xsitk_signed_maurer_dist


*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.