tf_census_transform — 2D `texture` op

• Data kinds: image → image

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

Usage

census_transform: the 3x3 non-parametric census bit-signature image.

For every pixel each of its 8 neighbours contributes one bit, set when the

centre exceeds the neighbour by more than a *relative* tolerance

`a * |centre| (a defaults the tolerance; b` unused). The 8 bits form

a value 0..255 rendered as [0,1]. Because the tolerance is relative and the

comparison is on ordering only, the signature is invariant to a global gain

(multiplying the image by any positive constant leaves every bit unchanged) --

the robustness-to-gain property that makes census matching useful for stereo.

Uses the raw (non-luma-collapsed) reflected border.

Detailed usage guide

• gallery2d_texture_freq 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_texture_freq — py -3.11 examples/gallery2d_texture_freq.py

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

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

Same category (`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).*

tf_census_transform — 2D texture op