Post-processing of PIV (particle image velocimetry) data typically contains three following stages: validation of the raw data, replacement of spurious and missing vectors, and some smoothing. A robust post-processing technique that carries out these steps simultaneously is proposed. The new all-in-one method (DCT–PLS), based on a penalized least squares approach (PLS), combines the use of the discrete cosine transform (DCT) and the generalized cross-validation, thus allowing fast unsupervised smoothing of PIV data. The DCT–PLS was compared with conventional methods, including the normalized median test, for post-processing of simulated and experimental raw PIV velocity fields. The DCT–PLS was shown to be more efficient than the usual methods, especially in the presence of clustered outliers. It was also demonstrated that the DCT–PLS can easily deal with a large amount of missing data. Because the proposed algorithm works in any dimension, the DCT–PLS is also suitable for post-processing of volumetric three-component PIV data.

中文翻译：

---

一种用于 PIV 数据自动后处理的快速一体化方法

PIV（粒子图像测速）数据的后处理通常包含以下三个阶段：原始数据的验证、伪向量和缺失向量的替换以及一些平滑处理。提出了一种同时执行这些步骤的强大的后处理技术。新的多合一方法 (DCT-PLS) 基于惩罚最小二乘法 (PLS)，结合了离散余弦变换 (DCT) 和广义交叉验证的使用，从而允许快速无监督地平滑 PIV数据。DCT-PLS 与传统方法进行了比较，包括归一化中值测试，用于模拟和实验原始 PIV 速度场的后处理。DCT-PLS 被证明比通常的方法更有效，尤其是在存在聚类异常值的情况下。还证明了 DCT-PLS 可以轻松处理大量缺失数据。由于所提出的算法适用于任何维度，因此 DCT-PLS 也适用于体积三分量 PIV 数据的后处理。