rank op• Data kinds: image → image
• Call: fullseye.apply(img, "mean_sp", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: mean_sp (the HALCON reference is a useful guide to its meaning and parameters)
*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).*
A robust smoothing filter. Returns the average of the 20th and 80th percentiles within the window (a trimmed mean), suppressing the influence of extreme bright/dark outliers (such as salt-and-pepper noise). a sets the window size to 3/5/7/9 (`_k(a)`). b is unused.
> The detailed description below is the original text — the summary and the headings are translated.
HALCON の `mean_sp`（ソルト&ペッパーノイズを抑制する平均化演算）に相当する近似 —— 上下 20% を除いた範囲の中点をとる点で単純平均よりノイズに強いが、HALCON 固有のアルゴリズムとは実装が異なる。
• 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.
mean_sp 0.50 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
rank)median · min_filter · max_filter · percentile · sk_median_disk · cv_median · median_image · median_rect
*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.