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- Publisher Website: 10.1145/3372261
- Scopus: eid_2-s2.0-85091966136
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Article: End-to-end Learned, Optically Coded Super-resolution SPAD Camera
Title | End-to-end Learned, Optically Coded Super-resolution SPAD Camera |
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Authors | |
Keywords | depth/transient imaging diffractive optics SPAD super-resolution |
Issue Date | 2020 |
Citation | ACM Transactions on Graphics, 2020, v. 39, n. 2, article no. 3372261 How to Cite? |
Abstract | Single Photon Avalanche Photodiodes (SPADs) have recently received a lot of attention in imaging and vision applications due to their excellent performance in low-light conditions, as well as their ultra-high temporal resolution. Unfortunately, like many evolving sensor technologies, image sensors built around SPAD technology currently suffer from a low pixel count. In this work, we investigate a simple, low-cost, and compact optical coding camera design that supports high-resolution image reconstructions from raw measurements with low pixel counts. We demonstrate this approach for regular intensity imaging, depth imaging, as well transient imaging. Our method uses an end-to-end framework to simultaneously optimize the optical design and a reconstruction network for obtaining super-resolved images from raw measurements. The optical design space is that of an engineered point spread function (implemented with diffractive optics), which can be considered an optimized anti-aliasing filter to preserve as much high-resolution information as possible despite imaging with a low pixel count, low fill-factor SPAD array. We further investigate a deep network for reconstruction. The effectiveness of this joint design and reconstruction approach is demonstrated for a range of different applications, including high-speed imaging, and time of flight depth imaging, as well as transient imaging. While our work specifically focuses on low-resolution SPAD sensors, similar approaches should prove effective for other emerging image sensor technologies with low pixel counts and low fill-factors. |
Persistent Identifier | http://hdl.handle.net/10722/315334 |
ISSN | 2023 Impact Factor: 7.8 2023 SCImago Journal Rankings: 7.766 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Sun, Qilin | - |
dc.contributor.author | Zhang, Jian | - |
dc.contributor.author | Dun, Xiong | - |
dc.contributor.author | Ghanem, Bernard | - |
dc.contributor.author | Peng, Yifan | - |
dc.contributor.author | Heidrich, Wolfgang | - |
dc.date.accessioned | 2022-08-05T10:18:30Z | - |
dc.date.available | 2022-08-05T10:18:30Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | ACM Transactions on Graphics, 2020, v. 39, n. 2, article no. 3372261 | - |
dc.identifier.issn | 0730-0301 | - |
dc.identifier.uri | http://hdl.handle.net/10722/315334 | - |
dc.description.abstract | Single Photon Avalanche Photodiodes (SPADs) have recently received a lot of attention in imaging and vision applications due to their excellent performance in low-light conditions, as well as their ultra-high temporal resolution. Unfortunately, like many evolving sensor technologies, image sensors built around SPAD technology currently suffer from a low pixel count. In this work, we investigate a simple, low-cost, and compact optical coding camera design that supports high-resolution image reconstructions from raw measurements with low pixel counts. We demonstrate this approach for regular intensity imaging, depth imaging, as well transient imaging. Our method uses an end-to-end framework to simultaneously optimize the optical design and a reconstruction network for obtaining super-resolved images from raw measurements. The optical design space is that of an engineered point spread function (implemented with diffractive optics), which can be considered an optimized anti-aliasing filter to preserve as much high-resolution information as possible despite imaging with a low pixel count, low fill-factor SPAD array. We further investigate a deep network for reconstruction. The effectiveness of this joint design and reconstruction approach is demonstrated for a range of different applications, including high-speed imaging, and time of flight depth imaging, as well as transient imaging. While our work specifically focuses on low-resolution SPAD sensors, similar approaches should prove effective for other emerging image sensor technologies with low pixel counts and low fill-factors. | - |
dc.language | eng | - |
dc.relation.ispartof | ACM Transactions on Graphics | - |
dc.subject | depth/transient imaging | - |
dc.subject | diffractive optics | - |
dc.subject | SPAD | - |
dc.subject | super-resolution | - |
dc.title | End-to-end Learned, Optically Coded Super-resolution SPAD Camera | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1145/3372261 | - |
dc.identifier.scopus | eid_2-s2.0-85091966136 | - |
dc.identifier.volume | 39 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | article no. 3372261 | - |
dc.identifier.epage | article no. 3372261 | - |
dc.identifier.eissn | 1557-7368 | - |
dc.identifier.isi | WOS:000583691000001 | - |