magnify op• 데이터 종류: video → table
• 호출: import motionmag; motionmag.motion_magnify(video, alpha, f_lo, f_hi, fps, scales: 'int' = 4, orientations: 'int' = 4) -> 'dict'(또는 opsmotionmag.get("motion_magnify"))
클립의 대역 내 움직임을 *alpha* 배로 -> `dict`.
> 아래 상세 설명은 원문입니다 —— 요약과 제목은 번역되어 있습니다.
For every oriented sub-band of every frame the local phase is taken relative
to that band's temporal mean as the wrapped deviation
`angle(z * conj(z_mean)) in (-pi, pi]` — it is deliberately not
unwrapped along time (see the design note above `_AMP_FLOOR`: unwrapping
a noise band is a random walk that manufactured a 12.27 rad step where
0.039 rad was intended) — band-passed to
`[f_lo, f_hi], multiplied by alpha - 1` and added back. Because a
translation by `d shifts a band's phase by -k·d`, the phase of the
result is `-alpha * k·d for *any* k` — the output displacement is
`alpha * d` without the local spatial frequency ever being estimated.
Low-pass, high-pass and completion residuals are reconstructed untouched
(they have no single `k` to be consistent about).
`alpha` is the displacement gain: 1 is the identity, 0 removes the
in-band motion, 2 doubles it, -1 reverses it. (The literature writes the
magnified motion as `(1 + alpha_paper) d; this alpha` is
`1 + alpha_paper`.)
Returns a dict::
{"video": (T, H, W) magnified frames,
"alpha": ..., "band_hz": (f_lo, f_hi), "fps": ...,
"snr_in": {...}, "snr_out": {...}, # raw band_snr of in / out
"image_snr_change_db": ..., # <= 0 once |alpha| > 1
"motion_snr_out_db": ..., # gain-corrected; never rises
"motion_snr_change_db": ...,
"band_power_ratio": ..., # 1.0 = perfectly linear
"phase_shift_max_rad": ..., "phase_shift_rms_rad": ...,
"linear_regime": bool, "reference_coherence": ...}
The SNR block is part of the contract, not decoration. Amplifying the
in-band phase amplifies the in-band noise by exactly the same factor, so
the *motion* SNR cannot rise — magnification reveals motion, it never
measures it better than the recording allowed. What degrades is the image:
the output's temporal fluctuation grows like `alpha^2` against an
unchanged static scene. Measured on a 64x64, 64-frame, 32 fps clip carrying
0.2 px of 4 Hz motion under sigma = 0.01 sensor noise, band 3-5 Hz:
====== =============== ================== ============== =============
alpha image_snr (dB) image change (dB) motion_snr_out band_power
(dB) ratio
====== =============== ================== ============== =============
1 29.2574 -0.0000 11.9404 1.000000
2 24.4304 -4.8270 11.6285 0.934861
4 18.9039 -10.3535 11.2270 0.857626
8 13.7428 -15.5146 9.7565 0.628551
====== =============== ================== ============== =============
Roughly 5 dB of image SNR per doubling (the algebra's asymptote is
`20*log10(2) = 6.02` once the amplified band dominates the noise budget),
while the motion SNR only ever falls. `band_power_ratio` is the measured
`band_power_out / (alpha^2 * band_power_in)`: 1.0 means the magnification
stayed linear, and the shortfall is the energy the phase modulation threw
into harmonics.
`phase_shift_max_rad` is the largest increment applied anywhere, including
in contrast-free bands that hold only noise, so it is routinely large and is
reported for completeness rather than as a verdict. `phase_shift_rms_rad`
is the contrast-weighted RMS — the number that describes the structure a
viewer actually sees — and `linear_regime is phase_shift_rms_rad < pi`.
`reference_coherence is |mean_t z| / mean_t |z|`, weighted by band
energy: it is 1 for small motion and collapses towards 0 when the motion is
large enough that the temporal-mean phase reference stops being meaningful
(see :func:phase_displacement for the closed form).
Narrow-band condition, measured. The relation is exact when each
sub-band carries a single moving component. On broadband texture (isotropic
noise smoothed by a Gaussian, 0.2 px of motion, `alpha = 3`) the recovered
magnified amplitude is 4.8 % low at sigma = 1.0, 5.5 % at 1.5 and 9.1 % at
3.0 px of smoothing — the more spatial frequencies share a band, the more
the phase of their sum departs from linearity in the displacement. That is
inherent to phase-based processing, not a tuning fault.
• motion_magnification 패밀리 가이드
• 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.
• motion_magnification — py -3.11 examples/motion_magnification.py
• quaternion_monogenic — py -3.11 examples/quaternion_monogenic.py
table 를 입력으로 받는 것)magnify)—
*Provenance: motionmag.py — MOTIONMAG 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.