xsk2_wiener — 2D `restoration` op

• Data kinds: image → image

• Call: fullseye.apply(img, "xsk2_wiener", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Wiener deconvolution (deblurring using a known point spread function). Calls `skimage.restoration.wiener`.

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

PSF はガウシアン形状を仮定して自前生成し、a が PSF の広がり

（標準偏差 `0.5 + 1.5*a`、5x5 窓）を振る。b がバランス項

（`0.05 + 0.5*b`。ノイズ対信号比の逆数に相当し、大きいほどノイズ

抑制寄りになる）を振る。**入力画像のボケが実際にこの想定ガウシアン

PSF と一致している場合にのみ有効**で、PSF の形が違うとリンギングや

復元失敗が出る。

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 (`restoration`)

xsk_inpaint · xsk_richardson_lucy · xsk_unwrap_phase · xcv_inpaint · xcv3_inpaint_ns · iv_richardson_lucy · iv_wiener_deconv_spatial · iv_unsharp_deblur

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

xsk2_wiener — 2D restoration op