Assessment and application of optical flow in background-oriented schlieren for compressible flows

Cakir, Bora O.; Lavagnoli, Sergio; Saracoglu, Bayindir H.; Fureby, Christer

doi:10.1007/s00348-022-03553-z

Cited by 18 publications

(3 citation statements)

References 54 publications

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“…Very few studies have performed a comparison of the two. Recently, Cakir et al (2023) has compared the performance of OF over cross-correlation to measure supersonic flows using Background Oriented Schlieren. They found that the OF-based reconstructions revealed superior characteristics of resolution and sensitivity over cross-correlation.…”

Section: Performance Of the Farneback Algorithm Versus Cross-correlat...mentioning

confidence: 99%

Comparison of Schlieren-based techniques for measurements of a turbulent and wavy free surface

Bheeroo

Mandel

2023

Preprint

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The free surface at an air-water interface can provide information regarding bathymetric complexities, as well as the subsurface flow. We present a comparison of the performance of two recent advances in light-based optical techniques for free surface measurements, Total Internal Reflection-Deflectometry and Moon-Glade Background Oriented Schlieren, with the more established method of Free-Surface Synthetic Schlieren. We make use of an optical flow algorithm over the more traditional Digital Image Correlation, in order to obtain higher spatial resolution data across the imaged free surface domain. The Optical flow algorithm presents additional benefits, such as computational efficiency and robustness in capturing large displacements and straining of tracked features. The three optical techniques are assembled in synchronization to image two free surface conditions: (1) a free surface being impinged upon by an underlying turbulent, free-shear flow and (2) a random and irregular wave field induced by a free jet. Using the high-resolution measurements, we provide insight on the emergence of multiple free surface dynamics for a turbulent free surface and dissect the local hydrodynamics of the free surface for several wave forcings. We present a comprehensive discussion on the benefits and drawbacks of each technique, including suggestions on the suitability of each technique for several experimental constraints.

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Section: Performance Of the Farneback Algorithm Versus Cross-correlat...mentioning

confidence: 99%

Comparison of Schlieren-based techniques for measurements of a turbulent and wavy free surface

Bheeroo

Mandel

2023

Preprint

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“…the obtained image and the background image. Compared to the cross correlation method based on the PIV, the optical flow method had higher resolution and accuracy (Cakir et al 2023)，so the optical flow method (Atcheson et al 2008) was chosen in this paper to obtain the displacement field.…”

Section: Data Acquisitionmentioning

confidence: 99%

Super resolution reconstruction of background oriented schlieren based on the convolution neural network with the gradient loss function

Xiangyu,

Hui,

Wang

et al. 2023

Preprint

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In order to refine the displacement field of the background oriented schlieren method, a super-resolution method based on deep learning has been newly proposed in the study, and were compared with the bicubic interpolation. The gradient loss functions were firstly introduced into the hybrid downsampled skip-connection/multi-scale (DSC/MS) model to improve the reconstruction effect. The reconstruction effects of the new loss functions were compared with that of the traditional MSE loss function. The results showed that the Laplace operator with average pooling had better performance than the origin loss function in all the indexes including PSNR, MSE, MSE of the gradient and the max MSE. In these four indexes, MSE of the gradient and the max MSE performed especially better than the others, where the MSE of the gradient reduced from 3.90E-05 to 3.30E-05 and the max MSE reduced from 0.392 to 0.360.

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“…Recently, dot tracking and optical flow (OF) methods have been adapted for BOS, in the cases of small local displacement fields Cakir et al (2022); Schmidt and Woike (2021); Rajendran et al (2019a). Dot tracking and OF methods can drastically increase the spatial resolution with OF methods providing pixel level displacement estimations.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Displacement Estimation Techniques for Background Oriented Schlieren of High-speed Compressible Turbulent Flows

Zhou,

Gaskins,

Poggie

et al. 2024

Preprint

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Background oriented schlieren (BOS) is a non-intrusive optical method for measuring density gradients in a fluid flow based on changes of local refractive index.The density gradients can be obtained by observing the displacement betweentwo images of a background pattern, with and without the presence of the flow.Existing methods to estimate displacements include block matching and optical flow. Image registration in computer vision seeks reasonable transformationsbetween two images such that one matches the other and has been under-utilizedin determining the displacement for BOS image processing. Deformable imageregistration (DIR) methods allow non-global transformations and are proposedas displacement estimation methods for processing BOS images. Numerical raytracing simulations are performed to generate synthetic BOS images of variousflows. The estimated density gradient results of block matching, optical flow,and DIR methods are compared to the ground truth (the path-averaged densitygradient of the schlieren object used in ray tracing) to assess and compare theirperformances. The performances of these methods are also validated on experimental BOS images to determine the displacement estimation method that ismost suitable for high-speed, turbulent flows.

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Assessment and application of optical flow in background-oriented schlieren for compressible flows

Cited by 18 publications

References 54 publications

Comparison of Schlieren-based techniques for measurements of a turbulent and wavy free surface

Comparison of Schlieren-based techniques for measurements of a turbulent and wavy free surface

Super resolution reconstruction of background oriented schlieren based on the convolution neural network with the gradient loss function

Comparison of Displacement Estimation Techniques for Background Oriented Schlieren of High-speed Compressible Turbulent Flows

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