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PIVlab – Towards User-friendly, Affordable and Accurate Digital Particle Image Velocimetry in MATLAB

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TLDR
The accuracy of several algorithms was determined and the best performing methods were implemented in a user-friendly open-source tool for performing DPIV flow analysis in Matlab.
Abstract
Digital particle image velocimetry (DPIV) is a non-intrusive analysis technique that is very popular for mapping flows quantitatively. To get accurate results, in particular in complex flow fields, a number of challenges have to be faced and solved: The quality of the flow measurements is affected by computational details such as image pre-conditioning, sub-pixel peak estimators, data validation procedures, interpolation algorithms and smoothing methods. The accuracy of several algorithms was determined and the best performing methods were implemented in a user-friendly open-source tool for performing DPIV flow analysis in Matlab.

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Long-range optofluidic control with plasmon heating.

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Detection of inter-frame forgeries in digital videos.

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References
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Journal ArticleDOI

The Design and Implementation of FFTW3

TL;DR: It is shown that such an approach can yield an implementation of the discrete Fourier transform that is competitive with hand-optimized libraries, and the software structure that makes the current FFTW3 version flexible and adaptive is described.
Book

Particle Image Velocimetry: A Practical Guide

TL;DR: In this paper, the authors present a practical guide for the planning, performance and understanding of experiments employing the PIV technique, which is primarily intended for engineers, scientists and students, who already have some basic knowledge of fluid mechanics and nonintrusive optical measurement techniques.
Journal ArticleDOI

Particle-Imaging Techniques for Experimental Fluid Mechanics

TL;DR: A review of these methods can be found in articles by Lauterborn & Vogel (1984), Adrian (1986a), Hesselink (1988), and Dudderar et al..
Journal ArticleDOI

Adaptive histogram equalization and its variations

TL;DR: It is concluded that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clip ahe can be made adequately fast to be routinely applied in the normal display sequence.
Journal ArticleDOI

Digital Particle Image Velocimetry

TL;DR: In this article, the directional ambiguity associated with PIV and LSV is resolved by implementing local spatial cross-correlations between two sequential single-exposed particle images, and the recovered velocity data are used to compute the spatial and temporal vorticity distribution and the circulation of the vortex ring.
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