texture op• Data kinds: image → image
• Call: fullseye.apply(img, "tf_rank_transform", 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).*
rank_transform: the local rank of each pixel among its neighbours.
Each pixel's value is the fraction of neighbours in a `(2r+1)x(2r+1)` window
that it strictly exceeds (`r = 1 + round(a*2); b` unused), i.e. its
ordinal rank normalized to [0,1]. Like the census transform it depends only on
pixel ordering, so it is invariant to a global gain: multiplying the image by
any positive constant leaves every rank unchanged (robust to illumination gain
for stereo/texture).
• gallery2d_texture_freq 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.
tf_rank_transform 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
texture)std_filter · gabor · sk_frangi · sk_meijering · sk_hessian · sk_gabor · sk_lbp · sk_entropy
*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.