Aberration Free Imaging via Speckle Pattern Encoding

2006 ◽  
Author(s):  
Eyal Ben-Eliezer ◽  
Emanuel Marom ◽  
Naim Konforti
2018 ◽  
Vol 26 (3) ◽  
pp. 3452 ◽  
Author(s):  
Pei Zhou ◽  
Jiangping Zhu ◽  
Hailong Jing

2019 ◽  
pp. 27-32
Author(s):  
A.D. Ivanov ◽  
V.L. Minaev ◽  
G.N. Vishnyakov ◽  
G.G. Levin
Keyword(s):  

2013 ◽  
Vol 63 (3) ◽  
pp. 30502
Author(s):  
Isabella Chiara Buscemi ◽  
Steve Guyot

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 90
Author(s):  
Shuo Zhu ◽  
Enlai Guo ◽  
Qianying Cui ◽  
Lianfa Bai ◽  
Jing Han ◽  
...  

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.


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