signal op• Datenarten: signal → signal
• Aufruf: import fullseye as fs; fs.ledger.local_std(x, window=9) (die Implementierung direkt: import dsp; dsp.local_std(x, window=9); aus dem Register: ops1d.get("local_std"))
Gleitende Standardabweichung mit angegebener Fehlerschranke.
> Die ausführliche Beschreibung unten ist der Originaltext — Zusammenfassung und Überschriften sind übersetzt.
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).
• Katalog der Beispieldaten (Download-URLs / Lizenzen) — 2-D nutzt skimage.data (BSD/Public Domain) plus synthetische Bilder, 3-D nennt Download-URLs echter Datenquellen (Stanford, PDS, …).
• Herkunft und Literatur der Operatoren — die Quellen der Forschung/Verfahren, auf denen diese Operatorfamilie beruht.
• Der kanonische Algorithmus (Autor, Jahr) und seine Anwendungen stehen im Familienleitfaden oben.
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
signal als Eingabe)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
signal)lowpass · highpass · bandpass · envelope · rms · quantize · companding_mu_law · resample
*Provenance: dsp.py — ONED Operator-Registry. Diese Notiz wird von tools/opdocs.py md erzeugt (nicht von Hand bearbeiten).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.