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)
An unsharp-mask-like sharpening filter (3x3 kernel convolution, OpenCV implementation). Convolves with a kernel whose center is `1+4a and whose top/bottom/left/right neighbors are -a` (at a=0 this is the identity kernel = no change; the larger a is, the stronger the discrete-Laplacian-like high-frequency boost), lifting the contrast near edges.
> The detailed description below is the original text — the summary and the headings are translated.
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。
• gallery2d_smoothing_rank family guide
• 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.
• gallery2d_smoothing_rank — py -3.11 examples/gallery2d_smoothing_rank.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.