typed op• Data kinds: rgbimage → image
• Call: fullseye.apply(img, "tb_specular_coefficient_map", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])
*The figure is the actual output on a synthetic 128×128 input. Left: input, right: output. Point clouds are drawn as a top-down scatter (brightness = z), 1-D series as a line plot, volumes as the maximum-intensity projection along z, videos as the middle frame, complex images as magnitude; return values that are not pictures are shown as the values themselves.*
*Knob a does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
*Knob b does not change the output (measured: identical at 0.1 / 0.5 / 0.9).*
Stages (the ops that come before → this op, left to right):
▸ tb_specular_coefficient_map: stages (docs site)
On other images (synthetic scene / photo / coins. Top row: inputs, bottom row: their outputs. Knobs at default):
▸ tb_specular_coefficient_map: other inputs (docs site)
The scalar interface (specular) coefficient of the dichromatic model. → (H, W).
The same decomposition as :func:specular_diffuse_split, returning the
scalar `m_s(x) instead of the coloured image m_s(x) * G`. That scalar
is what an inspection routine thresholds: it is the amount of light the
surface reflected *as a mirror does*, in the units of the input radiance,
and it is zero wherever the surface behaved as a Lambertian body.
`specular_coefficient_map(...) * illuminant_unit` equals the second return
value of :func:specular_diffuse_split exactly, by construction — the two
operators share one core.
Arguments, guards and honest limits are identical to
:func:specular_diffuse_split — including the fact that the two guards
bound gross violations only.
Raises `ValueError`: exactly the same conditions as
:func:specular_diffuse_split (invalid image, invalid illuminant,
identically zero image, body colour parallel to the illuminant, either
guard firing, fewer than 3 pixels on the uniform-body route, invalid
*body_rgb*).
Typed bridge of the specular op `specular_coefficient_map into the 2-D evolution registry: the same implementation, called under the op(v, a, b) convention. a drives max_rank_ratio (default 0.1) and b drives max_negative_frac` (default 0.02).
• 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 program below has been verified to run (same input as the figure). In Studio's help this block becomes buttons that load and run it on the spot.
img_to_rgb 0.50 0.50 tb_specular_coefficient_map 0.50 0.50
▸ Load this pipeline · Load & run
The examples below call the underlying ledger op specular_coefficient_map. This bridge op is the same implementation adapted to the fn(v, a, b) convention, so the behaviour carries over unchanged (only the call form differs).
• specular_photometric — py -3.11 examples/specular_photometric.py
image as input)identity · gaussian · mean_box · bilateral · unsharp · median · min_filter · max_filter
typed)tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal · tb_voxel_grid_downsample
*Provenance: ops.py — 2D 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.