signal op• 데이터 종류: signal → signal
• 호출: import fullseye as fs; fs.ledger.local_std(x, window=9)(구현을 직접 호출하려면 import dsp; dsp.local_std(x, window=9), 원장에서 가져오려면 ops1d.get("local_std"))
오차 한계를 함께 제시하는 이동 표준편차.
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
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).
• 샘플 데이터 카탈로그(DL URL / 라이선스) —— 2-D 는 skimage.data(BSD/public)+ 합성, 3-D 는 실데이터 소스(Stanford/PDS 등)의 DL URL.
• 연산자의 내력·참고문헌 —— 이 연산자 족의 바탕이 된 연구/기법의 출처.
• 알고리즘의 정전(저자·연도)과 용도는 위의 패밀리 사용 가이드에 적혀 있습니다.
• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py
signal 를 입력으로 받는 것)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 연산자 레지스트리. 이 op 노트는 tools/opdocs.py md 가 자동 생성합니다(직접 편집하지 마세요).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.