xsk2_reconstruction — 2D `morphology` op

• Data kinds: image → image

• Call: fullseye.apply(img, "xsk2_reconstruction", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Morphological reconstruction (reconstruction by dilation). Calls `skimage.morphology.reconstruction` with method="dilation".

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

シード画像を「元画像から a に応じた深さだけ暗くしたもの」

（`x - (0.05 + 0.25*a)`）として自動生成し、そのシードをマスク画像

（元画像そのもの）まで測地学的に膨張させる。a はシードの深さ（大きい

ほど多くの山が消える）を振る。b は未使用。小さな明るい斑点やノイズを

消しつつ、大きな構造の輪郭は保つ（オープニングより形状の崩れが少ない）。

Detailed usage guide

• gallery2d_morphology 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_morphology — py -3.11 examples/gallery2d_morphology.py

Ops the type connects to (they accept `image` as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (`morphology`)

gerode · gdilate · gopen · gclose · tophat · bothat · morph_grad · sk_area_opening

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

xsk2_reconstruction — 2D morphology op