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])
*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).*
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].
• gallery2d_physics_alife_3d 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.
tm_sinogram_denoise 0.50 0.50
▸ Load this pipeline · Load & run
• gallery2d_physics_alife_3d — py -3.11 examples/gallery2d_physics_alife_3d.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
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.