cv_sharpen — 2D `smoothing` op

• Data kinds: image → image

• Call: fullseye.apply(img, "cv_sharpen", 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

> This operator's description has not been translated yet. The original text follows as it is.

アンシャープ的な鮮鋭化フィルタ(3x3 カーネル畳み込み、OpenCV 実装)。中心 `1+4a、上下左右 -a` のカーネル(a=0 では単位カーネル=無変化、a が大きいほど離散ラプラシアン的な高域強調が強くかかる)を畳み込み、エッジ付近のコントラストを持ち上げる。

HALCON の emphasize(Enhance contrast of the image.)に相当(近似)。実装は `cv2.filter2D(v, kernel) を [0,1]` へ clip したもの —— a はカーネルの強さ(鮮鋭化の度合い)を 0〜1 に振る。b は未使用。

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_rank — py -3.11 examples/gallery2d_smoothing_rank.py

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

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

Same category (`smoothing`)

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

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

cv_sharpen — 2D smoothing op