xsk2_wiener — 2D restoration op

Data kinds: imageimage

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])

xsk2_wiener: 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

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.

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_wiener 0.50 0.50

▸ Load this pipeline  ·  Load & run

Runnable examples (verified samples that actually call this op)

gallery2d_smoothing_rankpy -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).*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.