smoothing op• Data kinds: image → image
• Call: fullseye.apply(img, "xsk3_rank_mean_bilateral", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*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).*
Local bilateral mean (skimage `filters.rank.mean_bilateral). An edge-preserving smoothing that, within the disk neighborhood, averages only the pixels falling within the range from s0 below to s1` above the center pixel's value.
> The detailed description below is the original text — the summary and the headings are translated.
`a は円盤半径(2+int(a*6) で 2〜8)と下方許容幅 s0(int(10+40*a) で 10〜50)の両方を兼ねる。b は上方許容幅 s1(int(10+40*b)` で 10〜50)を振る。
• 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.
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.
xsk3_rank_mean_bilateral 0.35 0.50
▸ Load this pipeline · Load & run
• 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.