smoothing op• Data kinds: image → image
• Call: fullseye.apply(img, "bilateral", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: bilateral_filter (the HALCON reference is a useful guide to its meaning and parameters)
Edge-preserving smoothing (bilateral filter). Equivalent to HALCON's `bilateral_filter` (bilateral filtering of an image.).
> The detailed description below is the original text — the summary and the headings are translated.
`a が空間方向の広がり σ_s = 1.0 + 3.0a を、b が明るさ方向の許容差 σ_r = 0.05 + 0.4b を振る。近傍窓は半径 r=2（5×5）固定で a では変わらない。近傍の重みは exp(-距離²/2σ_s²) × exp(-明度差²/2σ_r²)` の積で、明度差が大きい（=エッジをまたぐ）画素は重みが小さくなるため、平滑化しつつ輪郭を保てる。窓内を Python の二重ループで回すため他の平滑化 op より遅い。
• 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
• quickstart — py -3.11 examples/quickstart.py
image as input)identity · gaussian · mean_box · unsharp · median · min_filter · max_filter · percentile
smoothing)gaussian · mean_box · unsharp · 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.