Correcting artifacts from finite image size in Differential Dynamic Microscopy

Abstract

Differential Dynamic Microscopy (DDM) analyzes traditional real-space microscope images to extract information on sample dynamics in a way akin to light scattering, by decomposing each image in a sequence into Fourier modes, and evaluating their time correlation properties. DDM has been applied in a number of soft-matter and colloidal systems. However, objects observed to move out of the microscope's captured field of view, intersecting the edges of the acquired images, can introduce spurious but significant errors in the subsequent analysis. Here we show that application of a spatial windowing filter to images in a sequence before they enter the standard DDM analysis can reduce these artifacts substantially. Moreover, windowing can increase significantly the accessible range of wave vectors probed by DDM, and may further yield unexpected information, such as the size polydispersity of a colloidal suspension.

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• Uncertainty quantification and estimation in differential dynamic microscopy
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• Exploring particle dynamics in flowing complex fluids using differential dynamic microscopy
• The Hitchhiker's Guide to Differential Dynamic Microscopy
• Convolutional neural networks applied to differential dynamic microscopy reduces noise when quantifying heterogeneous dynamics
• Two Modes of Cluster Dynamics Govern the Viscoelasticity of Colloidal Gels