tb_smooth_funct_1d_mean — 2D typed op

• 資料種類:signal → signal

• 呼叫:fullseye.apply(img, "tb_smooth_funct_1d_mean", a=0.5, b=0.5)(2-D 的模型是一張圖 + 兩個純量旋鈕 a,b∈[0,1])

用法

迭代式移動平均平滑(HALCON `smooth_funct_1d_mean`)。

> 以下的詳細說明為原文 —— 摘要與標題已翻譯。

Applies a length-*size* uniform (box) filter *iterations* times with

`nearest` (edge-replicating) boundary handling. Repeated box filtering

approaches a Gaussian (central limit theorem).

:param y: 1-D function, at least 1 sample.

:param size: window length in samples; truncated to int, must be >= 1.

Even sizes are accepted but shift the window origin by half a sample

(scipy's origin convention) — prefer odd sizes for a symmetric window.

:param iterations: number of passes; truncated to int, must be >= 0.

`iterations=0` returns the (float64-coerced) input unchanged.

:returns: smoothed float64 array, same length as *y*.

:raises ValueError: non-1-D / NaN / Inf input, empty input, `size < 1`,

or `iterations < 0`.

Typed bridge of the 1d op `smooth_funct_1d_mean into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives size (default 3) and b drives iterations` (default 1).

參考(範例資料・文獻)

• 範例資料目錄(下載 URL / 授權) —— 2-D 用 skimage.data(BSD/公有領域)加合成圖,3-D 給出真實資料源(Stanford/PDS 等)的下載 URL。

• 運算子來歷與參考文獻 —— 該運算子族所依據的研究/方法出處。

可執行的範例(實際呼叫該運算子並已驗證的樣例)

• (尚無)

型別可銜接的下一個運算子(可接受 signal 作為輸入)

identity · tb_create_funct_1d_array · tb_smooth_funct_1d_gauss · tb_derivate_funct_1d · tb_integrate_funct_1d · tb_zero_crossings_funct_1d · tb_abs_funct_1d · tb_negate_funct_1d

同類別(typed)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D 運算子登記表。本條目由 tools/opdocs.py md 自動產生(請勿手動編輯)。*

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.