sk_median_disk — 2D `rank` op

• Data kinds: image → image

• Call: fullseye.apply(img, "sk_median_disk", 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)

Usage

Median filter with a disk-shaped footprint. Unlike a regular square kernel, this gives isotropic smoothing that is closer to circular.

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

HALCON の median_image(Compute a median filter with various masks.)に相当。実装は `filters.median(v, footprint=disk(1+int(a*3)))` —— a は円盤の半径を 1〜4 に振る(半径が大きいほど強く滑らかになるが細部も消える)。b は未使用。

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 · 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).*

sk_median_disk — 2D rank op