An optical flow algorithm based on gradient constancy assumption for PIV image processing
An optical flow algorithm based on gradient constancy assumption for PIV image processing
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DOI：
10.1088/1361-6501/aa6511
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发表时间：
2017-03
影响因子：
2.4
通讯作者：
Qianglong Zhong;Hua Yang;Z. Yin
中科院分区：
文献类型：
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作者：
Qianglong Zhong;Hua Yang;Z. Yin
粒子图像测速技术（PIV）作为一种流量测量技术已经成熟。它可以通过分析从数字记录图像中获得的粒子运动来描述流动的瞬时速度场。基于相关性的PIV评价技术以其良好的准确性和鲁棒性得到了广泛的应用。相关PIV技术虽然非常成功，但也存在一些弱点，这些弱点是基于光流的PIV算法可以避免的。目前，大多数用于PIV的光流方法都是基于亮度恒定假设。然而，由于流动成像技术的一些因素和流体的性质，使得亮度恒定假设在实际PIV情况下不太适用。本文介绍了一种基于梯度恒定假设的二维光流算法的实现。所提出的GCOF假设被照射的PIV粒子的边缘在运动过程中是恒定的。它包括两个项：局部-全局梯度数据的组合项和一阶散度和涡度平滑项。该方法可以提供精确的密集运动场。在合成图像和两个实验流上对该方法进行了测试。与其他光流算法的比较表明，该方法在光照变化条件下精度更高。GCOF与相关PIV技术的比较表明，GCOF在保持运动场的小散度和涡度结构以及获得较少的异常值方面具有优势。结果表明，GCOF能更准确、更好地描述湍流的拓扑结构。
Particle image velocimetry (PIV) has matured as a flow measurement technique. It enables the description of the instantaneous velocity field of the flow by analyzing the particle motion obtained from digitally recorded images. Correlation based PIV evaluation technique is widely used because of its good accuracy and robustness. Although very successful, correlation PIV technique has some weakness which can be avoided by optical flow based PIV algorithms. At present, most of the optical flow methods applied to PIV are based on brightness constancy assumption. However, some factors of flow imaging technology and the nature property of the fluids make the brightness constancy assumption less appropriate in real PIV cases. In this paper, an implementation of a 2D optical flow algorithm (GCOF) based on gradient constancy assumption is introduced. The proposed GCOF assumes the edges of the illuminated PIV particles are constant during motion. It comprises two terms: a combined local-global gradient data term and a first-order divergence and vorticity smooth term. The approach can provide accurate dense motion fields. The approach are tested on synthetic images and on two experimental flows. The comparison of GCOF with other optical flow algorithms indicates the proposed method is more accurate especially in conditions of illumination variation. The comparison of GCOF with correlation PIV technique shows that the proposed GCOF has advantages on preserving small divergence and vorticity structures of the motion field and getting less outliers. As a consequence, the GCOF acquire a more accurate and better topological description of the turbulent flow.