percentile — 2D `rank` op

• Data kinds: image → image

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

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

Usage

Rank filter for an arbitrary percentile. Equivalent to HALCON's `rank_image` (Compute a rank filter with arbitrary masks.).

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

`a が窓サイズを 3,5,7,9（_k(a)）に、b が抽出するパーセンタイルを 5〜95%（int(5+90b)）に振る。b が 0 に近いほど _min_filter、1 に近いほど _max_filter、中間で _median` に近づく——3 op を 1 つに統合した一般形。

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)

• color_transport — py -3.11 examples/color_transport.py

• gallery2d_smoothing_rank — py -3.11 examples/gallery2d_smoothing_rank.py

• image_quality_metrics — py -3.11 examples/image_quality_metrics.py

• representation_roundtrip — py -3.11 examples/representation_roundtrip.py

• vision_layout_from_catalog — py -3.11 examples/vision_layout_from_catalog.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 · sk_median_disk · cv_median · median_image · median_rect · median_separate

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

percentile — 2D rank op