itof op• Data kinds: depth → image2d
• Call: import fullseye as fs; fs.ledger.itof_flying_pixel_mask(depth, threshold_m=0.04, rel_threshold=0.0, radius=1, plateau_ratio=0.5, depth_sigma=None, n_sigma=3.0) (to call the implementation directly, import itof; itof.itof_flying_pixel_mask(depth, threshold_m=0.04, rel_threshold=0.0, radius=1, plateau_ratio=0.5, depth_sigma=None, n_sigma=3.0); from the registry, opsoptics.get("itof_flying_pixel_mask"))
Depth map → mask of flying pixels (pixels floating between foreground and background), (H, W) (1.0 = floating).
> The detailed description below is the original text — the summary and the headings are translated.
画素の視野が段差をまたぐと、iToF は 2 つの位相のフェーザ和を返し、距離は前景と背景の間に出る(段差の縁に沿って宙に浮いた点の列ができる)。ある方向(横・縦・2 つの斜め)の両側 ±r 画素の距離 a・b に対して、次の 3 つがそろったとき印をつける:
1. d が両者の間にある((d − a)(d − b) < 0)。
2. 両側との差がどちらも閾値 τ = max(threshold_m, rel_threshold · d, n_sigma · σ_d) を越える。*depth_sigma* (画素ごとの距離の雑音、itof_phase_amplitude の depth_sigma から作る)を渡すと、信号の弱い所(遠い床・暗い印刷)で雑音を段差と取り違えない。
3. 両側が平らな台地: その先の ±2r 画素との差 |a − a₂|・|b − b₂| が、それぞれ |d − a|・|d − b| の *plateau_ratio* 倍以下。★斜面(床を浅い角度で見る・傾いた面)は 1・2 を満たしてしまうが、斜面なら |a − a₂| ≈ |d − a|(同じ傾きが続く)なので 3 で落ちる。段差の縁の混合は、両側が前景と背景の平らな面なので残る。
r = 1〜*radius* を全部見る(縁の混合が 2 画素に広がる場合)。段差の上の正しい画素(前景か背景のどちらかに等しい)は、片側との差が 0 なので印がつかない。★幅 1〜2 画素の細い物(線・棒)は両側が背景で「間」にならないので、この判定では拾えない。
Raises ValueError: depth が 2 次元でない・非有限 / 閾値が負・両方 0 / radius が 1〜4 でない / plateau_ratio が (0, 1] でない / depth_sigma の形が合わない・負 / n_sigma が負。
Every optics op validates its input before computing (nothing slips through silently):
• Units are baked into the argument name — _mm / _um / _deg / _mrad. Confusing mm with µm does not crash; it yields a plausible-looking wrong answer, so the name prevents it. Nothing here guesses the unit from the magnitude.
• Strings raise ValueError — float('50') succeeds, so an unparsed configuration value would slip through as a length (measured: thin_lens('50', '200') returned a plausible 66.667 mm). bool is refused too, as the implicit promotion True == 1.
• complex / masked arrays raise ValueError (real-valued slots only; silently dropping the imaginary part or peeling off the mask is refused). NaN/Inf raises ValueError on every input.
• Division by zero and its relatives are refused by name: focal length 0, radius of curvature 0, refractive index <= 0, a fully opaque aperture (all zeros, so the normalisation is 0/0), a PSF whose sum is <= 0, a Stokes vector with S0 = 0, and an object sitting at the front focal point (the image is at infinity).
• Only two ops return a non-finite value, and both state it as a contract: depth_of_field returns far_mm = inf beyond the hyperfocal distance (that is what the hyperfocal distance means), and gaussian_beam returns wavefront_radius_mm = inf at the waist (the radius of curvature of a plane wavefront). Both also return a finite companion (far_is_infinite / curvature_per_mm). Any other silent NaN/Inf is detected internally and raises ValueError — "float64 overflowed" and "the answer is infinite" are different claims, so the first is never returned wearing the face of the second.
• Size caps: generated grids are capped by optics.MAX_GRID (4096); supplied fields/PSFs/apertures by optics.MAX_FIELD_ELEMENTS (2^24); ABCD element chains by optics.MAX_SYSTEM_ELEMENTS (1024); Zernike by MAX_ZERNIKE_TERMS (512) / MAX_ZERNIKE_ORDER (40) / MAX_ZERNIKE_BASIS (2^25). This closes, fail-closed, the paths where a small argument triggers a huge internal allocation (measured: n_max=40 × 4096² needs 108 GB).
• Physically impossible states are refused too: a Stokes vector with degree of polarisation > 1, negative transmittance, negative intensity, and invalid Zernike indices such as n-|m| odd.
• Sample-data catalog (download URLs / licences) — 2-D uses skimage.data (BSD/public domain) plus synthetic images; 3-D lists download URLs for real data sources (Stanford, PDS, …).
• Operator provenance and references — the sources of the research/methods this op family came from.
• The canonical algorithm (author, year) and its uses are named in the family usage guide above.
• poc_itof_multifreq — py -3.11 examples/poc_itof_multifreq.py
image2d as input)fraunhofer_pattern · pupil_psf · pupil_blur · psf_to_mtf · edge_spread · veiling_glare_index · emva_pair_statistics · emva_defect_pixels
itof)itof_capture · itof_phase_amplitude · itof_noise_budget · itof_unwrap_multifreq · itof_unwrap_error_rate · itof_multipath_separate · itof_wiggling_correct
*Provenance: itof.py — OPTICS operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.