Optical measurement of sound using time-varying laser speckle patterns

2011 ◽  
Author(s):  
Terence S. Leung ◽  
Shihong Jiang ◽  
Jeremy Hebden
Keyword(s):  
Optical Measurement ◽  
Laser Speckle ◽  
Time Varying ◽  
Speckle Patterns

scholarly journals Active dynamics of colloidal particles in time-varying laser speckle patterns

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Silvio Bianchi ◽  
Riccardo Pruner ◽  
Gaszton Vizsnyiczai ◽  
Claudio Maggi ◽  
Roberto Di Leonardo
Keyword(s):  
Colloidal Particles ◽  
Laser Speckle ◽  
Time Varying ◽  
Speckle Patterns

Identification of vulnerable atherosclerotic plaque by analysis of time-varying laser speckle patterns

2004 ◽  
Author(s):  
Seemantini K. Nadkarni ◽  
Brett E. Bouma ◽  
Tina Helg ◽  
Milan Singh Minsky ◽  
Raymond Chan ◽  
...  
Keyword(s):  
Atherosclerotic Plaque ◽  
Laser Speckle ◽  
Time Varying ◽  
Vulnerable Atherosclerotic Plaque ◽  
Speckle Patterns

scholarly journals Fourier transforms for fast and quantitative Laser Speckle Imaging

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
J. Buijs ◽  
J. van der Gucht ◽  
J. Sprakel
Keyword(s):  
Quantitative Data ◽  
Fourier Transforms ◽  
Imaging Technique ◽  
Laser Speckle ◽  
Frequency Range ◽  
Laser Speckle Imaging ◽  
Speckle Imaging ◽  
New Approach ◽  
Speckle Patterns ◽  
New Processing

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.

An artifact-metrics which utilizes laser speckle patterns for plastic ID card surface

2010 ◽  
Author(s):  
Manabu Yamakoshi ◽  
Xiaoying Rong ◽  
Tsutomu Matsumoto
Keyword(s):  
Laser Speckle ◽  
Speckle Patterns

Image synthesis from nonimaged laser-speckle patterns

1987 ◽  
Vol 12 (11) ◽  
pp. 858 ◽  
Author(s):  
Paul S. Idell ◽  
J. R. Fienup ◽  
Ron S. Goodman
Keyword(s):  
Image Synthesis ◽  
Laser Speckle ◽  
Speckle Patterns

scholarly journals Gradient Correlation Functions in Digital Image Correlation

2019 ◽  
Vol 9 (10) ◽  
pp. 2127 ◽  
Author(s):  
Mikael Sjödahl
Keyword(s):  
Correlation Function ◽  
Digital Image Correlation ◽  
Digital Image ◽  
Correlation Functions ◽  
Laser Speckle ◽  
Image Correlation ◽  
Intensity Correlation ◽  
Intensity Correlation Function ◽  
Speckle Patterns ◽  
The Difference

The performance of seven different correlation functions applied in Digital Image Correlation has been investigated using simulated and experimentally acquired laser speckle patterns. The correlation functions were constructed as combinations of the pure intensity correlation function, the gradient correlation function and the Hessian correlation function, respectively. It was found that the correlation function that was constructed as the product of all three pure correlation functions performed best for the small speckle sizes and large correlation values, respectively. The difference between the different functions disappeared as the speckle size increased and the correlation value dropped. On average, the random error of the combined correlation function was half that of the traditional intensity correlation function within the optimum region.

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