ring_artifact_apply — TOMOGRAPHY artifact op

数据种类:sinogramsinogram

调用:import tomography; tomography.ring_artifact_apply(sinogram, gain_sigma=0.02, seed=0, offsets=None)(或 opstomography.get("ring_artifact_apply"))

用法

给探测器加上逐 bin 的增益误差 —— 环状伪影之源。

> 以下的详细说明为原文 —— 摘要与标题已翻译。

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.

参考(示例数据・文献)

• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。

• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。

• 算法的正典(作者・年份)与用途见上面的族使用指南

可运行的示例(实际调用该算子并已验证的样例)

ct_reconstructionpy -3.11 examples/ct_reconstruction.py

类型可衔接的下一个算子(可接受 sinogram 作为输入)

backproject_sinogram · filtered_backprojection · sart_reconstruct · beam_hardening_apply · beam_hardening_correct · ring_artifact_remove · metal_trace_interpolate · sinogram_center_of_rotation

同类别(artifact)

beam_hardening_apply · beam_hardening_correct · ring_artifact_remove · metal_trace_interpolate


*Provenance: tomography.py — TOMOGRAPHY 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.