Single-pixel resolution ensemble correlation for micro-PIV applications

Westerweel, J.; Geelhoed, Peter; Lindken, Ralph

doi:10.1007/s00348-004-0826-y

Cited by 163 publications

(110 citation statements)

References 13 publications

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“…In the case of single-pixel evaluation, more images are required Westerweel et al 2004), and thus, 10,000 image pairs were generated for each particle image diameter considered in this analysis. For each pixel, the correlation function was computed using the approach outlined by Westerweel et al (2004).…”

Section: Single-pixel Ensemble-correlation: Resolution Limitmentioning

confidence: 99%

“…The position of the peak of this correlation map corresponds to the tracer particle (ensemble averaged) mean displacement, and the shape of the correlation yields the information about the average fluctuations. Single-pixel ensemble-correlation was first applied by Westerweel et al (2004) for stationary laminar flows in microfluidics. In the last years, the approach was extended for the analysis of periodic laminar flows (Billy et al 2004), of macroscopic laminar, transitional, and turbulent flows , and for compressible flows at large Mach numbers Bitter et al 2011).…”

Section: Introductionmentioning

confidence: 99%

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On the resolution limit of digital particle image velocimetry

2012

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This work analyzes the spatial resolution that can be achieved by digital particle image velocimetry (DPIV) as a function of the tracer particles and the imaging and recording system. As the in-plane resolution for window-correlation evaluation is related by the interrogation window size, it was assumed in the past that single-pixel ensemble-correlation increases the spatial resolution up to the pixel limit. However, it is shown that the determining factor limiting the resolution of single-pixel ensemblecorrelation are the size of the particle images, which is dependent on the size of the particles, the magnification, the f-number of the imaging system, and the optical aberrations. Furthermore, since the minimum detectable particle image size is determined by the pixel size of the camera sensor in DPIV, this quantity is also considered in this analysis. It is shown that the optimal magnification that results in the best possible spatial resolution can be estimated from the particle size, the lens properties, and the pixel size of the camera. Thus, the information provided in this paper allows for the optimization of the camera and objective lens choices as well as the working distance for a given setup. Furthermore, the possibility of increasing the spatial resolution by means of particle tracking velocimetry (PTV) is discussed in detail. It is shown that this technique allows to increase the spatial resolution to the subpixel limit for averaged flow fields. In addition, PTV evaluation methods do not show bias errors that are typical for correlation-based approaches. Therefore, this technique is best suited for the estimation of velocity profiles.

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Section: Single-pixel Ensemble-correlation: Resolution Limitmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the resolution limit of digital particle image velocimetry

2012

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“…For sum corr (raw a ), the single-correlation planes were normalized prior to averaging and for sum corr (raw b ) no normalization was done. A method to greatly increase the spatial resolution is the single-pixel ensemble correlation, is described by (Westerweel et al 2004;Kähler et al 2006). A signal is reconstructed for up to every pixel, containing all image information over the ensemble (in this case all 8,000 images).…”

Section: Tracking or Correlationmentioning

confidence: 99%

“…Using vector averaging, this erroneous vector has the same weight as all other vectors in the ensemble and causes a bias in the final result. Also, outliers in the data bias the averaged result towards zero, since it is assumed that outliers are randomly distributed with a zero mean (Westerweel et al 2004;Samarage et al 2011). Finally, the velocity is strongly underestimated.…”

Section: Tracking or Correlationmentioning

confidence: 99%

Particle imaging techniques for volumetric three-component (3D3C) velocity measurements in microfluidics

Cierpka

Kähler

2011

J Vis

131

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The reliable measurement of the 3D3C velocity field in microfluidic devices becomes more and more important for future optimization and developments for lab-on-a-chip applications or point-of-care medical diagnosis systems. In the past years, different particle-based imaging methods, such as confocal scanning microscopy, holography, stereoscopic and tomographic imaging or approaches based on defocused particle images or optical aberrations have been developed and applied successfully to measure velocity fields in microfluidic systems. The benefits and drawbacks of these methods will be discussed in detail as the proper understanding of the measurement principle is essential to select the most appropriate technique for a desired measurement application. Once an imaging method is chosen, the velocity can be estimated by correlation-based methods or tracking approaches. The advantages and disadvantages of both methods and the importance of image preprocessing will also be discussed in detail.

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“…The analysis of PIV recordings with single-pixel resolution or two-point ensemble correlation has been developed during the last years in order to enhance the spatial resolution and to increase the measurement accuracy of small scale flow phenomena (Westerweel et al 2004). In microfluids, this approach was first applied under the assumption of stationary flows.…”

Section: Introductionmentioning

confidence: 99%

Reynolds stress estimation up to single-pixel resolution using PIV-measurements

2011

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This article derives a theory for estimating Reynolds normal and shear stresses from PIV images with single-pixel resolution. The main idea is the analysis of the correlation function to identify the probability density function from which the Reynolds stresses can be derived in a 2-D regime. The work establishes a theoretical framework including the influence of the particle image diameter and the velocity gradients on the shape of the correlation function. Synthetic data sets are used for the validation of the proposed method. The application of the evaluation method on two experimental data sets shows that high resolution and accuracy are also obtained with experimental data. The approach is very general and can also be applied to correlation peaks that are obtained from sum-of-correlation PIV evaluations.

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Single-pixel resolution ensemble correlation for micro-PIV applications

Cited by 163 publications

References 13 publications

On the resolution limit of digital particle image velocimetry

On the resolution limit of digital particle image velocimetry

Particle imaging techniques for volumetric three-component (3D3C) velocity measurements in microfluidics

Reynolds stress estimation up to single-pixel resolution using PIV-measurements

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