xsk2_rank_geomean — 2D `rank` op

• Data kinds: image → image

• Call: fullseye.apply(img, "xsk2_rank_geomean", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

xsk2_rank_geomean: 入力 → 出力

*The figure is the real output on a synthetic 128×128 input. Left: input, right: output (a non-image return value is shown as the value itself).*

Usage

A type of rank filter, the geometric mean filter. Applies `skimage.filters.rank.geometric_mean to an 8-bit converted image using a circular structuring element (skimage.morphology.disk`).

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

a が構造要素の半径（`1 + int(a*3)`、範囲 1〜4）を振る。b は未使用。算術平均より暗い側（小さい値）に強く引っ張られるため、明るいスペックル状のノイズを抑えるのに向く。

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.

Try it in Studio

The program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.

xsk2_rank_geomean 0.50 0.50

▸ Load this pipeline · Load & run

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).*

xsk2_rank_geomean — 2D rank op