xsk2_radon — 2D `frequency` op

• Data kinds: image → image

• Call: fullseye.apply(img, "xsk2_radon", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Sinogram (projection data) via the Radon transform. Calls `skimage.transform.radon with a number of angles matched to the image's longer side (0-180 degrees, evenly spaced with linspace`), resizes the result back to the original image size, then normalizes by the maximum value.

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

a, b は未使用（角度本数は画像サイズから自動で決まる）。CT 再構成の

順投影に相当する処理で、直線状の構造ほどサイノグラム上に強いパターン

が出る。

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 (`frequency`)

lowpass · highpass · sk_butterworth · fft_image · power_real · power_byte · phase_rad · highpass_image

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

xsk2_radon — 2D frequency op