joint_bilateral — 3D `depth_denoise` op

• Data kinds: depth × image2d → depth

• Call: import depth_bilateral; depth_bilateral.joint_bilateral(depth: 'np.ndarray', guide: 'np.ndarray', spatial_sigma: 'float', range_sigma: 'float', *, invalid: 'float | None' = 0.0, truncate: 'float' = 3.0) -> 'np.ndarray' (or ops3d.get("joint_bilateral"))

Usage

Joint / cross bilateral: the depth is what gets smoothed, while the range weights come from the differences in the guide. → float64 (H,W).

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)

• sensor_seg — py -3.11 examples_3d/sensor_seg.py

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

depth_to_points · tsdf_from_depth · to_points · fuse_to_voxel · depth_to_organized_points · normals_from_depth · occlusion_edges · bearing_angle_image

Same category (`depth_denoise`)

bilateral_filter_depth · fill_holes

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

joint_bilateral — 3D depth_denoise op