xmh_selfmatch — 2D `self-similarity` op

• Data kinds: image → image

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

Usage

> This operator's description has not been translated yet. The original text follows as it is.

自己相似マップ(`mahotas.template_match` による自己テンプレートマッチング)。画像中心から切り出した小さなパッチを画像全体に対してテンプレートマッチングし、パッチに似た場所ほど 1 に近い値になるよう正規化して返す。

`a はパッチの半径(3+8 px 相当)を振る —— 大きくするほど広い範囲の類似度になる。b` は未使用。周期的なテクスチャや繰り返しパターンの検出に使える。

Detailed usage guide

• gallery2d_features 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_features — py -3.11 examples/gallery2d_features.py

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

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

Same category (`self-similarity`)

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

xmh_selfmatch — 2D self-similarity op