tb_sensor_capture — 2D `typed` op

• Data kinds: rgbimage → rgbimage

• Call: fullseye.apply(img, "tb_sensor_capture", a=0.5, b=0.5) (the 2-D model is one image plus two scalar knobs a,b∈[0,1])

Usage

Radiance → real-sensor output (shot noise, read noise, saturation, quantisation).

> The detailed description below is the original text — the summary and the headings are translated.

光子数 = radiance · exposure_ms · gain_e_per_unit / 1000 を平均とする Poisson。

そこへ読み出し雑音(正規)を足し、`full_well_e で**飽和**させ、bit_depth`

で量子化する。飽和は clip であって折り返さない(白飛びは白のまま)。

返り値は 0..2^bit_depth−1 の整数配列。`seed` を固定すれば決定的。

2-D 進化レジストリへ橋渡しした optics の op `sensor_capture。実装は同じで、呼び出し規約だけ op(v, a, b) に合わせてある。a が exposure_ms(既定 10)、b が gain_e_per_unit`(既定 50000)を振る。

References (sample data, literature)

• 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.

Runnable examples (verified samples that actually call this op)

• (none yet)

Ops the type connects to (they accept `rgbimage` as input)

identity · tb_wetness · tb_specular_diffuse_split · tb_specular_coefficient_map · tb_specular_free_transform · tb_rgb_to_quaternion

Same category (`typed`)

tb_points_to_voxel · tb_estimate_point_normals · tb_iss_keypoints · tb_angle_3points · tb_project_points · tb_render_point_depth · tb_statistical_outlier_removal · tb_radius_outlier_removal

*Provenance: ops.py — 2D operator registry. This per-op note is generated by tools/opdocs.py md (do not hand-edit).*

tb_sensor_capture — 2D typed op