imaging_sim op• Data kinds: image2d × table → image2d
• Call: import fullseye as fs; fs.ledger.render_through_lens(image, system, pixel_pitch_um=5.5, field_of_view=None, zones=3, noise=None, seed=0, illumination='traced', size=None, oversample=None) (to call the implementation directly, import lensimage; lensimage.render_through_lens(image, system, pixel_pitch_um=5.5, field_of_view=None, zones=3, noise=None, seed=0, illumination='traced', size=None, oversample=None); from the registry, opsoptics.get("render_through_lens"))
Render an ideal irradiance image as the sensor behind *system* would record it (image2d).
*image* (H×W, non-negative) is the ideal (paraxial) image on a sensor of *pixel_pitch_um* pixels centred on the optical axis; with *field_of_view* (half field to the sensor corner: degrees for an object at infinity, object height in mm otherwise) the picture is first zoomed so the corner sees that field. Pipeline: (a) inverse distortion remap (distortion_map grid, scipy.ndimage.map_coordinates order 1); (b) spatially varying blur — a zones×zones lattice of tile centres, each with its own pixel-integrated psf_from_opd (the +y-field PSF rotated to the tile azimuth), blended with bilinear (tent) weights so seams vanish; (c) relative illumination: "traced" = fraction of the field's ray bundle that reaches the image (vignetting, from raytrace.ray_bundle) normalised to the axis, times cos⁴ (obliquity, objects at infinity only), "cos4" = the classic law alone, "none"; (d) sensor, when *noise* is True or a dict {"full_well": 20000, "read_e": 3.0, "bits": 12, "exposure": 1.0, "dark_e": 0.0}: electrons = irradiance × exposure × full_well, Poisson shot noise (photoncount.photon_sample), Gaussian read noise, quantisation to *bits*, returned as DN/(2^bits − 1). With noise=None the float irradiance is returned untouched (deterministic; the noisy path is deterministic for a given *seed* too).
*oversample* defaults to whatever keeps at least 2 PSF samples per pixel (max(4, ceil(2·λ·F#/pitch))). Ground truth: a δ image through the f/2 paraboloid gives the pixel-integrated Airy PSF; a checkerboard through it comes back undistorted (correlation > 0.99); energy is conserved to 1 % with illumination off; noise off is bit-reproducible.
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.
• mv_cables — Cables (standards, speed, power delivery, robot cables)
• mv_cameras — Industrial camera makers (sensor mapping, line scan / TDI)
• mv_frame_grabbers — Frame grabber boards (not optics, but they decide whether you can capture at all)
• mv_image_sensors — Industrial image sensors (mainly current products)
• mv_standards — Camera interface standards and the bodies behind them
• virtual_machine_vision — Virtual machine vision — enumerating the parameters and an object model
• 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.
• lens_defect_dataset_demo — py -3.11 examples/lens_defect_dataset_demo.py
image2d as input)fraunhofer_pattern · pupil_psf · pupil_blur · psf_to_mtf · edge_spread · veiling_glare_index · emva_pair_statistics · emva_defect_pixels
imaging_sim)psf_from_opd · distortion_map · defect_dataset · calibration_views
*Provenance: lensimage.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.