fullseye

synthesize_translation — MOTIONMAG `synthesis` op

データ種: なし → video(引数だけで決まる op —— 画像やデータの入力を取らない)
呼び出し: import fullseye as fs; fs.ledger.synthesize_translation(shape=(64, 64), frames: 'int' = 32, amplitude_px=0.5, frequency_hz=4.0, fps=32.0, direction_deg=0.0, wavelength_px=(8.0, 16.0), contrast=0.4, offset=0.5, noise_sigma=0.0, seed: 'int' = 0) -> 'np.ndarray' (実装を直接呼ぶなら import motionmag; motionmag.synthesize_translation(shape=(64, 64), frames: 'int' = 32, amplitude_px=0.5, frequency_hz=4.0, fps=32.0, direction_deg=0.0, wavelength_px=(8.0, 16.0), contrast=0.4, offset=0.5, noise_sigma=0.0, seed: 'int' = 0) -> 'np.ndarray'、台帳から引くなら opsmotionmag.get("synthesize_translation"))

使い方

A clip whose displacement is known in closed form -> (T, H, W) video.

The scene is a stationary two-axis sinusoidal grating that is translated, frame by frame, by

``d(t) = amplitude_px * sin(2*pi * frequency_hz * t / fps)``

along direction_deg (0 deg = towards +x / increasing column). The translation is applied as a Fourier phase ramp, which for a pattern that is periodic on the grid is the exact band-limited shift — no interpolation kernel, no resampling error, so d(t) is ground truth to machine precision and sub-pixel amplitudes are meaningful.

wavelength_px is either one number (both axes) or (lambda_x, lambda_y). The default deliberately makes the two axes different octaves, and that is not cosmetic: if the horizontal and vertical gratings share a radial frequency they land in the same sub-band, whose local phase is then the phase of a sum of two moving components rather than of one. The phase of a sum is not linear in the displacement, so scaling it does not scale the motion — measured, a 64x64 clip built with a single wavelength on both axes magnified at alpha = 2 came out at 0.939 * (2 d) instead of 2 d, a 6.1 % error that does not shrink as d shrinks. Separating the octaves puts one component in each band and the relation becomes exact. This is the standard narrow-band condition of phase-based processing, made visible in the synthetic instead of hidden.

Each wavelength is snapped so that a whole number of cycles fits the frame (cycles = max(1, round(W / wavelength_px)), effective wavelength W / cycles); without that the pattern is not periodic on the grid and the Fourier shift would wrap a discontinuity across the border. With the default 64x64 frame and (8, 16) the snap is exact (8 and 4 cycles).

Values are not clipped into [0, 1]: clipping is a nonlinearity that would break the exact translation this function exists to provide. With the defaults the samples lie in [offset - contrast, offset + contrast].

noise_sigma adds zero-mean Gaussian sensor noise (after translation, drawn from numpy.random.default_rng(seed)) — the term that makes an SNR measurable at all.

This is the counterpart of photoncount.tcspc_simulate: a forward model good enough to close the loop on the analysis operators in this module.

詳しい使い方ガイド

motion_magnification ファミリガイド

参考(サンプルデータ・文献)

サンプルデータカタログ(DL URL / ライセンス) — 2-D は skimage.data(BSD/public)+ 合成、3-D は実データ源(Stanford/PDS 等)の DL URL。
演算子の来歴・参考文献 — この op 族の元になった研究/手法の出典。
アルゴリズムの正典(著者・年)と用途は上記ファミリ使い方ガイドに記載。

実行できる例(この op を実際に呼ぶ検証済みサンプル)

motion_magnification — py -3.11 examples/motion_magnification.py
poc_motion_magnification — py -3.11 examples/poc_motion_magnification.py
quaternion_monogenic — py -3.11 examples/quaternion_monogenic.py

型が繋がる次の op(`video` を入力に取れる)

temporal_bandpass · temporal_band_power · band_snr · motion_magnify · phase_displacement · displacement_series

同カテゴリ(`synthesis`)

—

Provenance: motionmag.py — MOTIONMAG operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。

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