temporal_bilateral — VIDEOSTREAM `denoise` op

• Data kinds: video → video

• Call: import videostream; videostream.temporal_bilateral(video, window: 'int' = 5, sigma_t: 'float' = 2.0, sigma_r: 'float' = 0.1) -> 'np.ndarray' (or opsvideostream.get("temporal_bilateral"))

Usage

Causal temporal bilateral denoise per frame → `(T, H, W) (video`).

Edge-preserving in time: averages recent frames but drops the weight of

frames that differ (moved), so it denoises static regions without ghosting

the motion the way :func:moving_average_window does.

Detailed usage guide

• video_streaming family guide

Background guides (the physics and conventions behind this op)

• mv_cables — ケーブル（規格・速度・給電・ロボットケーブル）

• mv_frame_grabbers — フレームグラバーボード（光学系ではないが、撮れるかを決める）

• mv_standards — カメラインターフェースの規格と団体

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.

• The canonical algorithm (author, year) and its uses are named in the family usage guide above.

Runnable examples (verified samples that actually call this op)

• video_streaming — py -3.11 examples/video_streaming.py

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

temporal_median_window · moving_average_window · background_subtraction_window · frame_difference_causal · exponential_background · exponential_foreground · running_mean_std · optical_flow_magnitude_stream

Same category (`denoise`)

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

temporal_bilateral — VIDEOSTREAM denoise op