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)
A general-purpose rank filter (`ndimage.percentile_filter) that sorts the pixel values in a window in ascending order and returns the value at the specified percentile position. It is a continuous generalization: percentile 0 corresponds to erosion, 100 to dilation, and 50 to median. Equivalent to HALCON's rank_image` (Compute a rank filter with arbitrary masks.) (HALCON can take an arbitrarily shaped mask, but here it is fixed to a square mask).
> The detailed description below is the original text — the summary and the headings are translated.
`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。
• 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.
• 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.