statistical_outlier_removal — 3D `preprocess` op

• Data kinds: points → points

• Call: import fullseye as fs; fs.ledger.statistical_outlier_removal(points, k: 'int' = 16, std_ratio: 'float' = 2.0) (to call the implementation directly, import pcl_filter; pcl_filter.statistical_outlier_removal(points, k: 'int' = 16, std_ratio: 'float' = 2.0); from the registry, ops3d.get("statistical_outlier_removal"))

• Return value through the ledger: fullseye.ledger.statistical_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.statistical_outlier_removal.raw(...) or call pcl_filter.statistical_outlier_removal directly.

• Underlying return: (kept, mask)

Usage

Remove the points whose mean distance to their k neighbours is a global outlier (statistical outlier removal).

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

点ごとに「最も近い k 個(自分自身は除く)までの平均距離」を測り、その全点分布の

`mean + std_ratio*std` を超える点を飛び点とみなして落とす。まばらな飛び点の掃除に

有効で、密な面上の点は残る。

Parameters

----------

points : array_like, shape (N, 3)

入力点群。

k : int

近傍数(既定 16)。点数が少なければ内部で `n-1` に丸める。

std_ratio : float

しきい値の緩さ。大きいほど残りやすい(除去が緩い)。

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)。`points[keep_mask] が filtered` に等しい。

Notes

-----

点数 < 3 では統計が立たないため、全点を残す(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`)

radius_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).*

statistical_outlier_removal — 3D preprocess op