rank_image — 2D `rank` op

• Data kinds: image → image

• Call: fullseye.apply(img, "rank_image", 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

> This operator's description has not been translated yet. The original text follows as it is.

窓内の画素値を昇順に並べて指定パーセンタイル位置の値を返す汎用ランク

フィルタ(`ndimage.percentile_filter`)。パーセンタイル 0 で収縮相当、

100 で膨張相当、50 でメディアン相当になる連続的な一般化。HALCON の

`rank_image`（Compute a rank filter with arbitrary masks.）に相当

(HALCON は任意形状マスクを取れるが、ここでは正方形マスクに固定)。

`a が窓の一辺を {3,5,7,9} で、b` がパーセンタイルを 5〜95% の

範囲で振る。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).*

rank_image — 2D rank op