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])
*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).*
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.
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.
xsk_richardson_lucy 0.50 0.50
▸ Load this pipeline · Load & run
• 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.