Polarization-based intensity correlation of a depolarized speckle pattern

2021 ◽  
Vol 46 (19) ◽  
pp. 4896
Author(s):  
Abhijit Roy ◽  
Maruthi M. Brundavanam
Keyword(s):  
Speckle Pattern ◽  
Intensity Correlation

Surface-roughness dependence of the intensity correlation function under speckle-pattern illumination

1990 ◽  
Vol 7 (12) ◽  
pp. 2254 ◽  
Author(s):  
Takeaki Yoshimura ◽  
Kazuo Kato ◽  
Kiyoshi Nakagawa
Keyword(s):  
Surface Roughness ◽  
Correlation Function ◽  
Speckle Pattern ◽  
Intensity Correlation ◽  
Intensity Correlation Function

Device for calibration of electronic speckle pattern interferometers

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

Study of Electronic Cards with Digital Speckle Pattern Interferometry

1990 ◽  
Vol 19 (1) ◽  
pp. 41-49
Author(s):  
R. S. Sirohi ◽  
T. S. Swaminathan
Keyword(s):  
Speckle Pattern ◽  
Digital Speckle Pattern Interferometry ◽  
Digital Speckle

Phase spectrum increments of the speckle pattern

2013 ◽  
Vol 63 (3) ◽  
pp. 30502
Author(s):  
Isabella Chiara Buscemi ◽  
Steve Guyot
Keyword(s):  
Speckle Pattern ◽  
Phase Spectrum

scholarly journals Speckle pattern creation methods for two‐dimensional digital image correlation strain measurements applied to mechanical tensile tests up to 700°C

Strain ◽  
2021 ◽  
Author(s):  
Phuong Luong ◽  
Rébecca Bonnaire ◽  
Jean‐Noel Périé ◽  
Quentin Sirvin ◽  
Luc Penazzi
Keyword(s):  
Digital Image Correlation ◽  
Digital Image ◽  
Speckle Pattern ◽  
Tensile Tests ◽  
Image Correlation ◽  
Two Dimensional ◽  
Strain Measurements ◽  
Mechanical Tensile

scholarly journals Locating and Imaging through Scattering Medium in a Large Depth

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 90
Author(s):  
Shuo Zhu ◽  
Enlai Guo ◽  
Qianying Cui ◽  
Lianfa Bai ◽  
Jing Han ◽  
...  
Keyword(s):  
Phase Space ◽  
Signal To Noise Ratio ◽  
Speckle Pattern ◽  
Heuristic Method ◽  
Scattering Medium ◽  
Scattering Media ◽  
Signal To Noise ◽  
Practical Applications ◽  
Large Depth ◽  
Strong Scattering

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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