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)
Remove the points whose mean distance to their k neighbours is a global outlier (statistical outlier removal).
For each point, measures "the mean distance to its k nearest neighbours (excluding itself)", and drops the points exceeding mean + std_ratio*std of that distribution over all points as flying points. Effective for cleaning up sparse flying points; points on dense surfaces remain.
points : array_like, shape (N, 3)
Input point cloud.
k : int
Number of neighbours (default 16). If there are few points, it is reduced internally to n-1.
std_ratio : float
Looseness of the threshold. Larger keeps more points (looser removal).
filtered : ndarray, shape (M, 3)
Surviving points (original order preserved).
keep_mask : ndarray of bool, shape (N,)
Whether to keep each input point (True = keep). points[keep_mask] equals filtered.
With fewer than 3 points no statistics can be formed, so all points are kept (graceful).
• depth_sensors — Depth sensors — ranging principles, real-device figures, how dropouts appear
• 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.
• pcl_geodesic — py -3.11 examples_3d/pcl_geodesic.py
points as input)points_to_voxel · gaussians_to_voxel · estimate_point_normals · to_points · match_points_ncc · match_pca · moment_axes · icp_point2point_3d
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).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.