frequency op• Data kinds: voxel → voxel
• Call: import fullseye as fs; fs.ledger.vol_fft_highpass(vol, cutoff, spacing=None) (to call the implementation directly, import volfreq; volfreq.vol_fft_highpass(vol, cutoff, spacing=None); from the registry, ops3d.get("vol_fft_highpass"))
Gaussian high-pass — the exact complement 1 - lowpass (the two sum to the input).
The sum holds to float precision, proven in tests. Removes the DC level and slow drift, keeps edges/texture. Output is signed (mean ~ 0).
The transfer function is 1 - exp(-|f|^2 / (2 cutoff^2)). The DC (f = 0) coefficient is 0, so the mean luminance is removed completely; at |f| = cutoff it is 1 - 0.61 ≈ 0.39, and it approaches 1 at higher frequencies. The return value is float64 of the same (D, H, W) as the input and is signed (contains negative values). To pass it to later stages that assume [0, 1] (display, vol_window_level etc.), normalise it with vol_stretch or use it in the form vol + highpass.
Arguments: cutoff is a positive finite value. With spacing=None it is cycles/voxel; passing spacing ((sz, sy, sx) or volio.VolumeMeta) makes it cycles/mm.
Validation (ValueError): same as vol_fft_lowpass (not 3-D / NaN or Inf / over MAX_VOXELS / invalid cutoff or spacing).
Where to use it: removing uneven illumination, thickness drift and background gradients (equivalent to subtracting the result of vol_fft_lowpass). Because the FFT treats the volume as periodic, luminance differences between faces leak through the wrap.
• 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.
• deconv_fft_restore — py -3.11 examples_3d/deconv_fft_restore.py
voxel as input)voxel_to_mips · voxel_to_mesh · signed_distance_field · to_points · sobel3d · hessian3d · curvature_maps · edt_jfa
frequency)vol_fft_lowpass · vol_fft_bandpass
*Provenance: volfreq.py — 3D 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.