local_std — ONED signal op

資料種類:signalsignal

呼叫: import fullseye as fs; fs.ledger.local_std(x, window=9)(要直接呼叫實作,import dsp; dsp.local_std(x, window=9);從台帳取用則 ops1d.get("local_std"))

用法

帶誤差界的移動標準差。

> 以下的詳細說明為原文 —— 摘要與標題已翻譯。

The 1-D counterpart of the image operator `local_std` (HALCON's

`deviation_image`): the variance is taken after subtracting the mean

(`E[x^2] - E[x]^2` loses its significant digits on a signal that sits far

from zero), unbiased by `n/(n-1)`, and the residual bias of the square root

removed by `c4(n), so the estimate of sigma` itself is unbiased.

*window* is the number of samples in the sliding window, **rounded up to the

next odd number** so the window can be centred (10 becomes 11). The error

bound below is computed from the window actually used, so the number quoted

stays true. The 2-D side does the same thing — `_k(a)` snaps the knob to

3/5/7/9 — and the typed bridge that exposes this op as `tb_local_std`

scales the knob continuously, so an even value arrives whenever the knob

lands between two odd ones.

**The relative standard error of each estimate is `1/sqrt(2(n-1))`** —

35 % for a 5-sample window, 11 % for 41. Quote it next to any noise figure:

a rolling sigma over 9 samples is +- 25 %, which is wider than most of the

changes people try to read off it.

Returns an array the same length as *x* (the ends are reflected).

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。

• 演算法的正典(作者・年份)與用途見上面的族使用指南

可執行的範例(實際呼叫該運算子並已驗證的樣例)

gallery2d_texture_freqpy -3.11 examples/gallery2d_texture_freq.py

型別可銜接的下一個運算子(可接受 signal 作為輸入)

create_funct_1d_array · create_funct_1d_pairs · smooth_funct_1d_gauss · smooth_funct_1d_mean · derivate_funct_1d · integrate_funct_1d · zero_crossings_funct_1d · local_min_max_funct_1d

同類別(signal)

lowpass · highpass · bandpass · envelope · rms · quantize · companding_mu_law · resample


*Provenance: dsp.py — ONED 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.