rank op• Data kinds: image → image
• Call: fullseye.apply(img, "median_image", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
• HALCON equivalent: median_image (the HALCON reference is a useful guide to its meaning and parameters)
Median filter (`ndimage.median_filter, square window). A denoising method that replaces each pixel with the median within a window; unlike a mean filter, it can remove salt-and-pepper noise while preserving edges. Equivalent to HALCON's median_image` (Compute a median filter with various masks.) (HALCON allows arbitrary masks such as circular or octagonal, 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}(_k(a))で振る。b` は未使用。
• 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_rect · median_separate
*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.