restoration op• Data kinds: image → image
• Call: fullseye.apply(img, "xsk_richardson_lucy", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
Richardson-Lucy deconvolution. Iteratively sharpens the image assuming the blur is a 3x3 mean kernel (box PSF) (calls `skimage.restoration.richardson_lucy` directly).
> The detailed description below is the original text — the summary and the headings are translated.
`a` が反復回数を 2〜17 回の範囲で振る(回数が多いほど強く先鋭化するが、
ノイズ増幅やリンギングも増える)。`b` は未使用。PSF は実際のぼけ量に関わらず
固定の 3x3 box を仮定するため、真の劣化過程と一致しない画像では改善が限定的、
または悪化することがある。
• gallery2d_smoothing_rank family guide
• 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.
• gallery2d_smoothing_rank — py -3.11 examples/gallery2d_smoothing_rank.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
restoration)xsk_inpaint · xsk_unwrap_phase · xcv_inpaint · xsk2_wiener · 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.