期刊
OPTICS LETTERS
卷 47, 期 19, 页码 5212-5215出版社
Optica Publishing Group
DOI: 10.1364/OL.465316
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类别
资金
- European Research Council [682080]
- Agencia Estatal de Investigacion [PID2019-105004GB-I00]
- Gobierno de Aragon [MP30_21]
- Key Technologies Research and Development Program of Guangzhou [202206010091]
- Science and Technology Planning Project of Guangdong Province [2019A050510034]
- Guangzhou Key Laboratory of Intelligent Agriculture [201902010081]
- European Research Council (ERC) [682080] Funding Source: European Research Council (ERC)
This study proposes a novel method to compactly represent time-resolved illumination using mixtures of exponentially modified Gaussians. The method is robust to noise, preserves structural information, and achieves consistent results and quantitative improvements in applications such as hidden-scene reconstruction and depth estimation.
Time-resolved illumination provides rich spatiotemporal information for applications such as accurate depth sensing or hidden geometry reconstruction, becoming a useful asset for prototyping and as input for data-driven approaches. However, time-resolved illumination measurements are high-dimensional and have a low signal-to-noise ratio, ham-pering their applicability in real scenarios. We propose a novel method to compactly represent time-resolved illumi-nation using mixtures of exponentially modified Gaussians that are robust to noise and preserve structural information. Our method yields representations two orders of magnitude smaller than discretized data, providing consistent results in such applications as hidden-scene reconstruction and depth estimation, and quantitative improvements over previous approaches. (c) 2022 Optica Publishing Group
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