Applying Feature Detection to XPCS Image Processing

Abstract Sequential X-ray photon correlation spectroscopy (XPCS) reveals sample dynamics by analyzing a series of coherent scattering images, which is often time-consuming. For applications like real-time XPCS analysis, high efficiency is desired. Pixel binning is a straightforward strategy to reduce the processing time, but over-binning may result in an insufficient signal-to-noise ratio. In this work, feature detection is applied to obtain the optimal binning factor for the XPCS image processing. Results show that under optimal binning, the processing time is reduced by more than one order of magnitude. In addition, it is illustrated that feature detection could potentially be applied to other coherent imaging and scattering techniques such as coherent diffraction imaging (CDI).