Computational 3D and reflectivity imaging with high photon efficiency
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Shapiro_Computational 3d.pdf
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1.76 MB
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Author(s)
Shin, Dongeek
Kirmani, Ahmed
Shapiro, Jeffrey H.
Goyal, Vivek K.
Date Issued
October 2014
Journal
Proceedings of the 2014 IEEE International Conference on Image Processing (ICIP)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Shin, Dongeek, Ahmed Kirmani, Vivek K Goyal, and Jeffrey H. Shapiro. “Computational 3D and Reflectivity Imaging with High Photon Efficiency.” 2014 IEEE International Conference on Image Processing (ICIP) (October 2014).
Version
Author's final manuscript
Abstract
Capturing depth and reflectivity images at low light levels from active illumination of a scene has wide-ranging applications. Conventionally, even with single-photon detectors, hundreds of photon detections are needed at each pixel to mitigate Poisson noise. We introduce a robust method for estimating depth and reflectivity using on the order of 1 detected photon per pixel averaged over the scene. Our computational imager combines physically accurate single-photon counting statistics with exploitation of the spatial correlations present in real-world reflectivity and 3D structure. Experiments conducted in the presence of strong background light demonstrate that our computational imager is able to accurately recover scene depth and reflectivity, while traditional maximum likelihood-based imaging methods lead to estimates that are highly noisy. Our framework increases photon efficiency 100-fold over traditional processing and thus will be useful for rapid, low-power, and noise-tolerant active optical imaging.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICIP.2014.7025008
