artifact op• 資料種類:sinogram → sinogram
• 呼叫:import tomography; tomography.ring_artifact_apply(sinogram, gain_sigma=0.02, seed=0, offsets=None)(或 opstomography.get("ring_artifact_apply"))
給偵測器加上逐 bin 的增益誤差 —— 環狀偽影之源。
> 以下的詳細說明為原文 —— 摘要與標題已翻譯。
A detector bin whose gain is `g reports I = g I_true`, so after the
logarithm the line integral picks up a constant offset `-ln g` at that
bin, the same at every angle. Back-projecting a constant column smears it
around the rotation axis, and the reconstruction grows a ring at the radius
that bin's rays are tangent to. One bad pixel, one perfect circle.
The offsets are drawn once from `N(0, gain_sigma)` with a fixed *seed* and
applied to every row, because the whole point is that the error does not
vary with angle — that is what distinguishes a ring from noise, and what makes
:func:ring_artifact_remove possible.
:param sinogram: `(n_angles, n_detectors)`.
:param gain_sigma: standard deviation of the per-bin offset, `>= 0`.
:param seed: RNG seed; there is no `None` (determinism is a contract here).
:param offsets: explicit `(n_detectors,)` offsets; overrides the random draw.
:returns: `(n_angles, n_detectors)` float64 sinogram.
:raises ValueError: on a negative sigma, a non-int seed, or an *offsets* whose
length is not the detector count.
• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。
• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。
• 演算法的正典(作者・年份)與用途見上面的族使用指南。
• ct_reconstruction — py -3.11 examples/ct_reconstruction.py
sinogram 作為輸入)backproject_sinogram · filtered_backprojection · sart_reconstruct · beam_hardening_apply · beam_hardening_correct · ring_artifact_remove · metal_trace_interpolate · sinogram_center_of_rotation
artifact)beam_hardening_apply · beam_hardening_correct · ring_artifact_remove · metal_trace_interpolate
*Provenance: tomography.py — TOMOGRAPHY 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.