tm_sinogram_denoise — 2D tomography op

• Data kinds: image → image

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

Usage

Smooth the input sinogram along the ANGLE direction (rows). Neighbouring projection angles view almost the same object, so angle-direction smoothing is a genuine consistency prior that suppresses per-angle detector noise while preserving the sinusoidal traces. `a sets the angle-axis Gaussian sigma (a*4), b adds a gentle detector-axis sigma (b*1.5`). Output stays a same-shape sinogram in [0,1].

Detailed usage guide

• gallery2d_physics_alife_3d 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_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py

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

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

Same category (tomography)

tm_radon_forward · tm_fbp_reconstruct · tm_sart_reconstruct · tm_backproject_unfiltered

*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.