xsk3_rank_subtract_mean — 2D gray op

Data kinds: imageimage

Call: fullseye.apply(img, "xsk3_rank_subtract_mean", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Local mean subtraction (skimage `filters.rank.subtract_mean`). Returns the difference obtained by subtracting the mean brightness of the disk neighborhood from each pixel. The skimage implementation scales the difference to 1/2 and shifts it to the middle of the range, to avoid underflow. It cancels global light/dark unevenness and enhances local contrast.

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

`a は円盤半径(1+int(a*4) で 1〜5)を振る。b` は未使用。8bit 量子化を経由するため元の float64 精度は失われる。

Detailed usage guide

gallery2d_gray_arith 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_gray_arithpy -3.11 examples/gallery2d_gray_arith.py

Ops the type connects to (they accept image as input)

identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter

Same category (gray)

gamma · invert · scale_clip · equalize · sigmoid · clahe · sk_adapthist · sk_enhance_contrast


*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.