Reverse hierarchical PIV processing
Reverse hierarchical PIV processing
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DOI：
10.1088/0957-0233/13/7/304
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发表时间：
2002-06
影响因子：
2.4
通讯作者：
J. Rohály;F. Frigerio;D. Hart
中科院分区：
文献类型：
--
作者：
J. Rohály;F. Frigerio;D. Hart
为了有效提高PIV图像中粒子图像位移检测的空间分辨率和动态范围，提出了一种新的分层处理方案。该技术充分利用了离散相关函数的多分辨率特性，在最小尺度上开始处理，并在必要时基于层间相关校正和验证的结果逐步将相关平面构建到更大的询问区域。结果表明，该算法可以在直接相关算法和基于FFT的相关算法中实现，大大降低了计算复杂度。该技术为考虑流场、播撒和成像异常的局部自适应超分辨率处理开辟了新的前景。以最低比例(例如，像素或粒子图像大小)进行的处理允许在任何形状上组合相关平面。因此，所提出的反向分层处理在大小和形状上都代表了询问区域的优化，以最大化相关面信噪比。该方法在实验获得的图像上得到了成功的演示。
A novel hierarchical processing scheme is proposed to efficiently increase the spatial resolution and dynamic range of detecting particle image displacements in PIV images. The technique takes full advantage of the multi-resolution characteristic of the discrete correlation function by starting the processing at the smallest scale and, if necessary, gradually building correlation planes into larger interrogation areas based on the result of inter-level correlation correction and validation. It is shown that the algorithm can be implemented in both direct and FFT based correlation algorithms with greatly reduced computational complexity. The technique opens new perspectives for locally adaptive super-resolution processing taking flow field, seeding, and imaging anomalies into account. Processing at the lowest scale (e.g. pixel or particle image size) allows the combination of correlation planes on any shape. Hence the proposed reverse hierarchical processing represents interrogation area optimization both in size and shape in order to maximize the correlation plane signal-to-noise ratio. The method is successfully demonstrated on experimentally obtained images.