Theory and practical recommendations for autocorrelation-based image correlation spectroscopy

Abstract

Abstract. Image correlation spectroscopy (ICS) is a powerful technique for detecting arrangement of fluorophores in images. This tutorial gives background into the mathematical underpinnings of ICS, specifically image autocorrelation. The effects of various artifacts and image processing steps, including background subtraction, noise, and image morphology were examined analytically and their effects on ICS analysis modeled. A series of recommendations was built based on this analysis.