fullseye

photon_sample — PHOTON counting op

使い方

Poisson-sample an expected-photon image into an actual photon count image.

image is a non-negative 2-D map of scene radiance in arbitrary units; lambda = image * photons_per_unit + dark_rate is the expected number of photons in each pixel over the exposure, and the result is one Poisson realisation of it. dark_rate is the dark-count contribution (a SPAD counts thermally generated carriers even in the dark) in the same photon units.

Returns the counts themselves as a float64 (H, W) image (integer valued). That is the deliberate difference from :func:backends_aug.aug_shot_noise, which returns Poisson(v*K)/K clipped to [0, 1] for training-data augmentation: every operator downstream here (Fano factor, Anscombe, Coates, dToF) needs N, and the rescale-and-clip is not invertible.

seed is a required non-negative integer and the RNG is numpy.random.default_rng(seed) — same seed, same frame, on any machine.

Ground truth it reproduces (pinned in tests/test_photoncount.py): the sample mean and sample variance both converge to lambda. Measured on a flat lambda = 100 field of 512x512 pixels at seed 0 — mean 99.9796, Fano factor 1.001089, so the photon-limited SNR is sqrt(lambda): 9.9990 predicted from the mean, 9.9935 actually achieved.

Raises ValueError: negative or non-finite image, negative photons_per_unit / dark_rate, a non-integer or negative seed, an image over :data:MAX_IMAGE_ELEMENTS, and — instead of letting numpy fail deep inside the sampler — any lambda over :data:MAX_LAMBDA.

詳しい使い方ガイド

参考(サンプルデータ・文献)

実行できる例(この op を実際に呼ぶ検証済みサンプル)

型が繋がる次の op(image2d を入力に取れる)

photon_statistics · photon_uncertainty · anscombe_transform · anscombe_inverse

同カテゴリ(counting)

photon_statistics · photon_uncertainty


Provenance: photoncount.py — PHOTON operator registry. この per-op ノートは tools/opdocs.py md が自動生成(手編集しない)。

© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.