mls_smooth — 3D preprocess op

• Data kinds: points → points

• Call: import pcl_filter; pcl_filter.mls_smooth(points, radius: 'float', order: 'int' = 2) (or ops3d.get("mls_smooth"))

Usage

Drop noise by projecting each point onto a local polynomial surface (Moving Least Squares smoothing).

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 · radius_outlier_removal · voxel_grid_downsample · 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.