local_std — ONED 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"))

사용법

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).

참고(샘플 데이터·문헌)

• 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.

실행 가능한 예제(이 연산자를 실제로 호출하는 검증된 샘플)

• gallery2d_texture_freq — py -3.11 examples/gallery2d_texture_freq.py

타입이 이어지는 다음 연산자(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

같은 카테고리(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.