Speckle images have found multiple applications in image-based measurement techniques, where the objective of measurement is the estimation of speckle displacements between two often consecutive images. Depending on the characteristics of a measurement system and its measurands, the signal-to-noise ratio (SNR) of recorded images may become low and even marginal. One solution to improve the accuracy of speckle displacement estimation in such cases is the use of super-resolution methods. In this article a robust and versatile partial differential equation based resolution enhancement method is presented for the analysis of low SNR speckle displacement signals. The application of the method to synthetic one-dimensional and two-dimensional signals as well as actual particle displacement images indicate that the method is capable of reducing noise effects and partially recovering lost correlation, which in turn makes the selection of smaller interrogation windows and achieving higher resolution and accuracy of displacement estimation possible. The method is applicable to both speckle and particle displacement images.

斑点图像在基于图像的测量技术中发现了多种应用，其中测量的目的是估计两个经常连续的图像之间的斑点位移。根据测量系统及其测量对象的特性，记录图像的信噪比（SNR）可能会变低，甚至变得微不足道。在这种情况下提高散斑位移估计准确性的一种解决方案是使用超分辨率方法。在本文中，提出了一种鲁棒且通用的基于偏微分方程的分辨率增强方法，用于分析低SNR散斑信号。该方法在合成的一维和二维信号以及实际的粒子位移图像上的应用表明，该方法能够减少噪声影响并部分恢复丢失的相关性，从而可以选择较小的询问窗口并实现更高的分辨率和更高的位移估计精度。该方法适用于斑点图像和颗粒位移图像。