rank_rect — 2D rank op

• Data kinds: image → image

• Call: fullseye.apply(img, "rank_rect", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

• HALCON equivalent: rank_rect (the HALCON reference is a useful guide to its meaning and parameters)

Usage

The implementation is identical to `rank_image (kind: "rank", a percentile filter over a square window). In HALCON, rank_image (arbitrary mask) and rank_rect (restricted to rectangular masks) are separate operators, but in this stand-in both point to the same square-window implementation. A stand-in for HALCON's rank_rect` (Compute a rank filter with rectangular masks.).

> The detailed description below is the original text — the summary and the headings are translated.

`a が窓の一辺、b` がパーセンタイル(5〜95%)を振る。両方が使われる。

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 (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.