radius_outlier_removal — 3D `preprocess` op

• Data kinds: points → points

• Call: import fullseye as fs; fs.ledger.radius_outlier_removal(points, radius: 'float', min_neighbors: 'int' = 8) (to call the implementation directly, import pcl_filter; pcl_filter.radius_outlier_removal(points, radius: 'float', min_neighbors: 'int' = 8); from the registry, ops3d.get("radius_outlier_removal"))

• Return value through the ledger: fullseye.ledger.radius_outlier_removal(...) returns **only the declared out type points** (the underlying function also returns auxiliary values). When you need what was dropped, use fullseye.ledger.radius_outlier_removal.raw(...) or call pcl_filter.radius_outlier_removal directly.

Usage

Remove the points with fewer than min_neighbors neighbours within radius (isolated-point removal).

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

各点を中心に半径 `radius の球を張り、その中に居る他点の数が min_neighbors`

に満たない点を「孤立した粒」として落とす。統計的手法より局所的・直接的で、

センサの実スケールが分かっているときにしきい値を決めやすい。

Parameters

----------

points : array_like, shape (N, 3)

入力点群。

radius : float

近傍とみなす球の半径(> 0)。

min_neighbors : int

残すのに必要な近傍数(自分自身は数えない、既定 8)。

Returns

-------

filtered : ndarray, shape (M, 3)

生き残った点(元の順序を保持)。

keep_mask : ndarray of bool, shape (N,)

各入力点を残すか(True=残す)。

Notes

-----

`radius <= 0` は ValueError。空入力は空を返す(graceful)。

Background guides (the physics and conventions behind this op)

• depth_sensors — 深度センサの知識 — 測距原理・実機の値・欠測の出方

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.

Runnable examples (verified samples that actually call this op)

• pcl_geodesic — py -3.11 examples_3d/pcl_geodesic.py

Ops the type connects to (they accept `points` as input)

points_to_voxel · gaussians_to_voxel · estimate_point_normals · to_points · match_points_ncc · match_pca · moment_axes · icp_point2point_3d

Same category (`preprocess`)

statistical_outlier_removal · voxel_grid_downsample · mls_smooth · volume_downsample

*Provenance: pcl_filter.py — 3D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

radius_outlier_removal — 3D preprocess op