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- Title
Locating and Imaging through Scattering Medium in a Large Depth.
- Authors
Zhu, Shuo; Guo, Enlai; Cui, Qianying; Bai, Lianfa; Han, Jing; Zheng, Dongliang
- Abstract
Scattering medium brings great difficulties to locate and reconstruct objects especially when the objects are distributed in different positions. In this paper, a novel physics and learning-heuristic method is presented to locate and image the object through a strong scattering medium. A novel physics-informed framework, named DINet, is constructed to predict the depth and the image of the hidden object from the captured speckle pattern. With the phase-space constraint and the efficient network structure, the proposed method enables to locate the object with a depth mean error less than 0.05 mm, and image the object with an average peak signal-to-noise ratio (PSNR) above 24 dB, ranging from 350 mm to 1150 mm. The constructed DINet firstly solves the problem of quantitative locating and imaging via a single speckle pattern in a large depth. Comparing with the traditional methods, it paves the way to the practical applications requiring multi-physics through scattering media.
- Subjects
SPECKLE interference; SIGNAL-to-noise ratio; DEEP learning
- Publication
Sensors (14248220), 2021, Vol 21, Issue 1, p90
- ISSN
1424-8220
- Publication type
Letter
- DOI
10.3390/s21010090