Diffusion in SPAD Signals
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866912853927133184 |
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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 |