Hybrid particle image velocimetry with the combination of cross-correlation and optical flow method

Yang, Zifeng; Johnson, Mark

doi:10.1007/s12650-017-0417-7

Cited by 26 publications

(7 citation statements)

References 28 publications

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“…The distortions in the checkerboard images were analyzed using the FCD method described in section 2 and the random dot images were processed with a hybrid DIC+OF scheme, akin to that proposed by Yang and Johnson [30]. An outline of the computational steps involved in both schemes is given in Fig.…”

Section: Implementation Of the Distortion Tracking Algorithmsmentioning

confidence: 99%

Real-time quantitative Schlieren imaging by fast Fourier demodulation of a checkered backdrop

Wildeman

2018

Exp Fluids

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A quantitative synthetic Schlieren imaging (SSI) method based on fast Fourier demodulation is presented. Instead of a random dot pattern (as usually employed in SSI), a 2D periodic pattern (such as a checkerboard) is used as a backdrop to the refractive object of interest. The range of validity and accuracy of this "Fast Checkerboard Demodulation" (FCD) method are assessed using both synthetic data and experimental recordings of patterns optically distorted by small waves on a water surface. It is found that the FCD method is at least as accurate as sophisticated, multi-stage, digital image correlation (DIC) or optical flow (OF) techniques used with random dot patterns, and it is significantly faster. Efficient, fully vectorized, implementations of both the FCD and DIC/OF schemes developed for this study are made available as open source Matlab scripts.

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Section: Implementation Of the Distortion Tracking Algorithmsmentioning

confidence: 99%

Real-time quantitative Schlieren imaging by fast Fourier demodulation of a checkered backdrop

Wildeman

2018

Exp Fluids

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“…Depending on how the constraint is provided, the methods are grouped into two categories: a local method first proposed by Lucas-Kanade (1981) and a global method pioneered by Horn-Schunk (1981). In this study, we used a global optical flow method following the recent studies on the optical flow application to PIV (Ruhnau et al 2005;Corpetti et al 2006;Heitz et al 2008;Liu et al 2015;Cassisa et al 2011;Derian et al 2013;Yang and Johnson 2017;Cai et al 2018). However, the brightness constancy assumption may not be guaranteed for PIV depending on the set-up and synchronization of a laser and a camera.…”

Section: Robust Optical Flow Against Intensity Changesmentioning

confidence: 99%

“…They used the displacement field estimated using cross correlation to initialize the problem and to be refined. Yang and Johnson (2017) suggested refining displacement field obtained by direct correlation without sub-pixel interpolation using Liu and Shen (2008) estimator.…”

Section: Introductionmentioning

confidence: 99%

Velocity refinement of PIV using global optical flow

et al. 2019

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In this study, we propose a method to enhance the particle image velocimetry (PIV) velocity resolution by using global optical flow along with image warping. A global optical flow formula proposed by Brox et al. ( 2004) is adopted to compensate the intensity changes of PIV image pairs, which depend on the set-up and synchronization of a laser and a camera. The proposed method is quantitatively evaluated and validated using synthetic particle image pairs generated for Rankine vortices and reference DNS-based velocity data. The proposed method outperforms the conventional PIV method in capturing small scale vortex and turbulent structures due to its enhanced spatial resolution. In addition, the proposed method shows good performance in large displacement fields and varying image intensity whereas optical flow is applicable to small displacement and susceptible to image intensity variation in general. Finally, the proposed method is applied to real PIV particle images of a multiple rectangular jet flow. The results show that the proposed method successfully works out high-resolution fluid mechanical structure and quantities while preserving the conventional PIV results.

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“…Consequently, the refined velocity vectors can be obtained. The hybrid methods were studied by Yang et al [14] and Liu et al [15]. In those studies, similar cross-correlation and optical-flow algorithms were applied.…”

Section: Introductionsmentioning

confidence: 99%

Optical-Flow and Cross-Correlation Algorithms for Analyzing Jet Flow

Hùng¹,

Anh²,

Văn³

2022

TNUJST

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Xử lý dữ liệu nhằm thu được trường vận tốc toàn cục rất quan trọng trong cơ học chất lỏng.Nghiên cứu này trình bày thuật toán lai để trích xuất véc tơ vận tốc từ ảnh của phương pháp đo vận tốc ảnh hạt (PIV) thực hiện trong quá trình thực nghiệm. Phương pháp lai sử dụng cả thuật toán tương quan chéo và thuật toán xử lý ảnh. Đầu tiên, thuật toán tương quan chéo được sử dụng để trích xuất vận tốc ban đầu từ ảnh PIV. Sau đó, thuật toán xử lý ảnh được áp dụng cho các trường vận tốc đã được tinh chỉnh với ước lượng ban đầu bằng kết quả tương quan chéo. Phương pháp đề xuất được áp dụng cho phân tích véc tơ vận tốc từ dòng chảy qua vòi phun. Kết quả chỉ ra rằng phương pháp lai thấy hình ảnh tương tự với thuật toán tương quan chéo. Ngoài ra, độ phân giải đã được cải thiện nhiều bởi thuật toán được đề xuất so với kết quả từ phương pháp tương quan chéo. Cả trường vận tốc trung bình và vận tốc tức thời được phân tích trong nghiên cứu này. Ảnh hưởng của hệ số Lagrange, số bước lặp tính toán lên kết quả của phương pháp lai được khảo sát. Phương pháp được đề xuất cho thấy hiệu quả cao trong việc trích xuất trường vận tốc từ ảnh PIV.

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Hybrid particle image velocimetry with the combination of cross-correlation and optical flow method

Abstract: Johnson, Mark Bradley. M.

Cited by 26 publications

References 28 publications

Real-time quantitative Schlieren imaging by fast Fourier demodulation of a checkered backdrop

Real-time quantitative Schlieren imaging by fast Fourier demodulation of a checkered backdrop

Velocity refinement of PIV using global optical flow

Optical-Flow and Cross-Correlation Algorithms for Analyzing Jet Flow

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