xsp_savgol — 2D `smoothing` op

• Data kinds: image → image

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

Usage

Smooths the image with a Savitzky-Golay filter (applied one-dimensionally, column direction first then row direction).

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

`a は窓幅を 5, 7, 9, 11, 13 の奇数に振る（w = 5 + 2*int(a*4)`）。

多項式次数は 2 に固定。`b` は未使用。窓内に 2 次多項式を最小二乗

フィットして中心値を置き換える手法なので、単純な移動平均よりピークの

高さや勾配を保ったまま平滑化できる。窓幅が画像サイズに対して大きすぎると

境界の処理（`scipy` の既定の外挿）の影響が強く出る。

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 (`smoothing`)

gaussian · mean_box · bilateral · unsharp · sk_tv · sk_wavelet · sk_rolling_ball · sk_nlm

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

xsp_savgol — 2D smoothing op