Toward absolute flow speed monitoring with robust quantitative single-exposure laser speckle imaging with noise correction and static scattering removal (Conference Presentation)

Author(s):  
Xinlin Chen ◽  
Chenge Wang ◽  
M. Xu
2014 ◽  
Vol 22 (17) ◽  
pp. 21079 ◽  
Author(s):  
Hao Li ◽  
Qi Liu ◽  
Hongyang Lu ◽  
Yao Li ◽  
Hao F. Zhang ◽  
...  

2016 ◽  
Vol 42 (1) ◽  
pp. 57 ◽  
Author(s):  
Yang Wang ◽  
Dong Wen ◽  
Xiao Chen ◽  
Qin Huang ◽  
Ming Chen ◽  
...  

2014 ◽  
Vol 39 (3) ◽  
pp. 678 ◽  
Author(s):  
J. C. Ramirez-San-Juan ◽  
R. Ramos-Garcia ◽  
G. Martinez-Niconoff ◽  
B. Choi

2021 ◽  
Author(s):  
Ilya Balmages ◽  
Janis Liepins ◽  
Dmitrijs Bliznuks ◽  
Stivens Zolins ◽  
Ilze Lihacova ◽  
...  

2019 ◽  
Vol 122 ◽  
pp. 52-59 ◽  
Author(s):  
AmirHessam Aminfar ◽  
Nami Davoodzadeh ◽  
Guillermo Aguilar ◽  
Marko Princevac

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
J. Buijs ◽  
J. van der Gucht ◽  
J. Sprakel

Abstract Laser speckle imaging is a powerful imaging technique that visualizes microscopic motion within turbid materials. At current two methods are widely used to analyze speckle data: one is fast but qualitative, the other quantitative but computationally expensive. We have developed a new processing algorithm based on the fast Fourier transform, which converts raw speckle patterns into maps of microscopic motion and is both fast and quantitative, providing a dynamnic spectrum of the material over a frequency range spanning several decades. In this article we show how to apply this algorithm and how to measure a diffusion coefficient with it. We show that this method is quantitative and several orders of magnitude faster than the existing quantitative method. Finally we harness the potential of this new approach by constructing a portable laser speckle imaging setup that performs quantitative data processing in real-time on a tablet.


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