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Autores principales: Dvir, Lior, Torem, Nadav, Schechner, Yoav Y.
Formato: Preprint
Publicado: 2026
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Acceso en línea:https://arxiv.org/abs/2601.07599
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author Dvir, Lior
Torem, Nadav
Schechner, Yoav Y.
author_facet Dvir, Lior
Torem, Nadav
Schechner, Yoav Y.
contents We derive the likelihood of a raw signal in a single photon avalanche diode (SPAD), given a fixed photon flux. The raw signal comprises timing of detection events, which are nonlinearly related to the flux. Moreover, they are naturally stochastic. We then derive a score function of the signal. This is a key for solving inverse problems based on SPAD signals. We focus on deriving solutions involving a diffusion model, to express image priors. We demonstrate the effect of low or high photon counts, and the consequence of exploiting timing of detection events.
format Preprint
id arxiv_https___arxiv_org_abs_2601_07599
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Diffusion in SPAD Signals
Dvir, Lior
Torem, Nadav
Schechner, Yoav Y.
Computer Vision and Pattern Recognition
We derive the likelihood of a raw signal in a single photon avalanche diode (SPAD), given a fixed photon flux. The raw signal comprises timing of detection events, which are nonlinearly related to the flux. Moreover, they are naturally stochastic. We then derive a score function of the signal. This is a key for solving inverse problems based on SPAD signals. We focus on deriving solutions involving a diffusion model, to express image priors. We demonstrate the effect of low or high photon counts, and the consequence of exploiting timing of detection events.
title Diffusion in SPAD Signals
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2601.07599