entropy_image — 2D `texture` op

• Data kinds: image → image

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

• HALCON equivalent: entropy_image (the HALCON reference is a useful guide to its meaning and parameters)

Usage

An image obtained by normalizing the grayscale Shannon entropy within a circular window (`skimage.filters.rank.entropy, 8-bit quantized). A texture measure of the "spread" of gray levels within the window: low in uniform regions and high in regions where diverse gray levels mix. Corresponds to HALCON's entropy_image` (Calculate the entropy of gray values within a rectangular window) -- an approximation using a circular window here versus HALCON's rectangular window.

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

`a が窓の半径を 1〜4 の範囲(_rad(a))で振る。b` は未使用。skimage

が無い環境ではこの分岐は呼べない。

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).*

entropy_image — 2D texture op