piv_line_integral_convolution — PIV visualise op

• Data kinds: flow2d → image2d

• Call: import pivops; pivops.piv_line_integral_convolution(flow, length=12, upsample=4, seed=0) (or opspiv.get("piv_line_integral_convolution"))

Usage

> This operator's description has not been translated yet. The original text follows as it is.

線積分畳み込み(LIC)—— 流れに沿って白色雑音をぼかした模様の画像。

ベクトルの矢印は密にすると潰れ、疎にすると構造を見落とす。LIC は画素ごと

に流線に沿って雑音を平均するので、密度の選択が要らない。向きの情報は落ちる

(前後を区別しない)ので、回転の向きを見たいときは矢印か色相図と併用する。

Args:

flow: `(2, h, w)`。

length: 流線に沿って積分する片側の歩数。長いほど滑らかになるが、

渦の芯のような曲率の大きい場所では構造が伸びて嘘になる。

upsample: 出力の解像度倍率(格子は粗いので拡大してから積分する)。

seed: 白色雑音の種。

Returns:

`(h * upsample, w * upsample)` float64、値域 [0, 1]。

Detailed usage guide

• piv_displacement family guide

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)

• (none yet)

Ops the type connects to (they accept image2d as input)

piv_cross_correlate · piv_multipass · piv_deform_pass · strain_from_displacement · correlation_quality · speckle_quality

Same category (visualise)

piv_flow_to_rgbimage

*Provenance: pivops.py — PIV 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.