论文标题
通过傅立叶变换计算结构函数，在DDM分析中提高了性能
Increased performance in DDM analysis by calculating structure functions through Fourier transform in time
论文作者
论文摘要
差异动态显微镜（DDM）是光学显微镜与统计分析的组合，以获取有关从软物质物理到生物学的各种样品的动态行为的信息。在DDM中，样品的动力学演变以不同的长度尺度分别研究，并从不同时间记录的一组图像中提取。感兴趣的特定结果是可以通过空间傅立叶变换和信号差异来计算的结构函数。在这项工作中，我们提出了一种算法，以根据DDM分析方案有效地处理一组图像。我们在以前的工作中报道的最先进的算法上贴上了新方法。由于时间的额外变换，而不是执行信号差异，新的实现将更快地计算DDM分析。这也允许在基于CPU的机器中获得非常快速的分析。为了测试新代码，我们在有没有GPU硬件加速的情况下对1000多个图像组进行了DDM分析。例如，对于$ 512 \ times 512 $像素的图像，新算法的速度比以前的GPU代码快10倍。没有GPU硬件加速度，对于相同的图像，我们发现新算法比仅在CPU上运行的旧算法要快300。
Differential Dynamic Microscopy (DDM) is the combination of optical microscopy to statistical analysis to obtain information about the dynamical behaviour of a variety of samples spanning from soft matter physics to biology. In DDM, the dynamical evolution of the samples is investigated separately at different length scales and extracted from a set of images recorded at different times. A specific result of interest is the structure function that can be computed via spatial Fourier transforms and differences of signals. In this work, we present an algorithm to efficiently process a set of images according to the DDM analysis scheme. We bench-marked the new approach against the state-of-the-art algorithm reported in previous work. The new implementation computes the DDM analysis faster, thanks to an additional Fourier transform in time instead of performing differences of signals. This allows obtaining very fast analysis also in CPU based machine. In order to test the new code, we performed the DDM analysis over sets of more than 1000 images with and without the help of GPU hardware acceleration. As an example, for images of $512 \times 512$ pixels, the new algorithm is 10 times faster than the previous GPU code. Without GPU hardware acceleration and for the same set of images, we found that the new algorithm is 300 faster than the old one both running only on the CPU.
