counting op• 数据种类:image2d → image2d
• 调用:import photoncount; photoncount.photon_uncertainty(counts, relative=False, zero_floor=0.0)(或 opsphoton.get("photon_uncertainty"))
光子计数帧逐像素的泊松误差棒。
> 以下的详细说明为原文 —— 摘要与标题已翻译。
For a Poisson variable the variance *equals* the mean, so the one-sigma
uncertainty of a single measurement `N is sqrt(N)` — no calibration, no
noise model to fit. With `relative=True` the returned map is the relative
uncertainty `1/sqrt(N)` instead (its reciprocal is the per-pixel SNR).
*zero_floor* replaces counts below it before the square root. It exists
because `N = 0 gives sqrt(0) = 0`, i.e. "this pixel is exactly zero
with no uncertainty", which is wrong: the 95% Poisson upper limit for a
single observed zero is about 3 photons. Set `zero_floor=1.0` for the
common "one-count prior" convention. It is not applied silently — the
default is 0.0 and the absolute map really does return 0 there.
Returns a float64 `(H, W)` image.
Raises `ValueError`: negative, non-finite or non-2-D *counts*, a
negative *zero_floor*, and — instead of returning `inf` —
`relative=True` with any pixel at 0 after the floor (that is the division
`1/sqrt(0); pass zero_floor > 0` to say what a zero should mean).
• 示例数据目录(下载 URL / 许可证) —— 2-D 用 skimage.data(BSD/公有领域)加合成图,3-D 给出真实数据源(Stanford/PDS 等)的下载 URL。
• 算子来历与参考文献 —— 该算子族所依据的研究/方法出处。
• 算法的正典(作者・年份)与用途见上面的族使用指南。
• photon_timeresolved — py -3.11 examples/photon_timeresolved.py
image2d 作为输入)photon_sample · photon_statistics · anscombe_transform · anscombe_inverse
counting)photon_sample · photon_statistics
*Provenance: photoncount.py — PHOTON 算子登记表。本条目由 tools/opdocs.py md 自动生成(请勿手工编辑)。*
© 2026 Kazufumi Furuse — Fullseye operator documentation. Licensed under Apache-2.0.