unsharp — 2D smoothing op

Data kinds: imageimage

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

HALCON equivalent: emphasize (the HALCON reference is a useful guide to its meaning and parameters)

Usage

Unsharp mask. ★It clips to [0,1] on the way out (2026-09-02).

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

`v + k*(v - blur)` は定義上オーバーシュートする(実測 min=-0.1499 /

max=+1.1499)。_apply は段間で同じ clip を掛けるので **パイプライン結果は

ビット不変**だが、fullseye.apply を単発で呼ぶ経路だけは生値が出ていて、

image の [0,1] 契約を破ったまま保存すると黒/白に潰れていた。GPU 側

(accel._unsharp)も同じ clip を持つ。

Detailed usage guide

gallery2d_smoothing_rank 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_smoothing_rankpy -3.11 examples/gallery2d_smoothing_rank.py

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

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

Same category (smoothing)

gaussian · mean_box · bilateral · sk_tv · sk_wavelet · sk_rolling_ball · sk_nlm · sk_tv_bregman


*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.