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Abstract / Description of output
Photon counting lidar has become an invaluable tool for 3D depth imaging due to the fine-precision it can achieve over long ranges. However, high frame rate, high resolution lidar devices produce an enormous amount of time-of-flight (ToF) data which can hinder the deployment of real-time systems. In this paper, an efficient photon acquisition approach is proposed that exploits the simplicity of piecewise polynomial splines to form a hardware-friendly compressed statistic, or spline sketch, of the ToF data. We show that a piecewise linear or quadratic spline sketch, requires minimal on-chip arithmetic computation per photon detection and can reconstruct real-world depth images using a simple closed form solution. Further, by building range-walk correction into the proposed estimation algorithms, it is demonstrated that the spline sketches can be made robust to photon pile-up effects.
Original language | English |
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Title of host publication | ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 1-5 |
Number of pages | 5 |
ISBN (Electronic) | 978-1-7281-6327-7 |
ISBN (Print) | 978-1-7281-6328-4 |
DOIs | |
Publication status | Published - 10 Jun 2023 |
Event | ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - Rhodes Island, Greece Duration: 4 Jun 2023 → 10 Jun 2023 |
Conference
Conference | ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
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Period | 4/06/23 → 10/06/23 |
Keywords / Materials (for Non-textual outputs)
- Laser radar
- Three-dimensional displays
- Signal processing algorithms
- Signal processing
- Hardware
- Real-time systems
- System-on-chip
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Dive into the research topics of 'Hardware Friendly Spline Sketched Lidar'. Together they form a unique fingerprint.Projects
- 1 Finished
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C-SENSE: Exploiting low dimensional models in sensing, computation and signal processing
1/09/16 → 31/08/22
Project: Research