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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.22806 |
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| _version_ | 1866911320356421632 |
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| author | Choi, Seungman Menart, Peter Schramka, Andrew Jape, Shubhankar Bauer, Leif Park, In-Yong Jacob, Zubin |
| author_facet | Choi, Seungman Menart, Peter Schramka, Andrew Jape, Shubhankar Bauer, Leif Park, In-Yong Jacob, Zubin |
| contents | Ground-based imaging systems struggle to achieve diffraction-limited resolution when atmospheric turbulence and photon scarcity act simultaneously. In this regime, conventional adaptive optics, speckle imaging, and blind deconvolution lack sufficient information diversity to reliably estimate either the scene or the turbulence. We present Turbulence Aware Poisson Blind Deconvolution (TAP-BD), a framework designed for robust image recovery in these extreme conditions. TAP-BD extracts more information from coded-detection through phase diversity and decodes it with a physics-informed optimization that incorporates low photon Poisson statistics. Experiments show that TAP-BD provides reliable reconstructions of both scene and turbulence using only a few tens of measurements, even under strong aberrations and photon-starved conditions where existing methods fail. This capability enables photon-efficient, turbulence resilient imaging for applications such as space situational awareness and long-range remote sensing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_22806 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Photon-starved imaging through turbulence at the diffraction limit Choi, Seungman Menart, Peter Schramka, Andrew Jape, Shubhankar Bauer, Leif Park, In-Yong Jacob, Zubin Optics Instrumentation and Detectors Ground-based imaging systems struggle to achieve diffraction-limited resolution when atmospheric turbulence and photon scarcity act simultaneously. In this regime, conventional adaptive optics, speckle imaging, and blind deconvolution lack sufficient information diversity to reliably estimate either the scene or the turbulence. We present Turbulence Aware Poisson Blind Deconvolution (TAP-BD), a framework designed for robust image recovery in these extreme conditions. TAP-BD extracts more information from coded-detection through phase diversity and decodes it with a physics-informed optimization that incorporates low photon Poisson statistics. Experiments show that TAP-BD provides reliable reconstructions of both scene and turbulence using only a few tens of measurements, even under strong aberrations and photon-starved conditions where existing methods fail. This capability enables photon-efficient, turbulence resilient imaging for applications such as space situational awareness and long-range remote sensing. |
| title | Photon-starved imaging through turbulence at the diffraction limit |
| topic | Optics Instrumentation and Detectors |
| url | https://arxiv.org/abs/2510.22806 |