Correlation and variational approaches for motion and diffusion estimation in fluorescence imaging

In this paper we compare correlation-based and variational approaches for both motion and diffusion estimation in fluorescence imaging. The so-called Spatio-Temporal Image Correlation Spectroscopy (STICS) is widely used in fluorescence imaging to recover physical parameters such as directional flow or diffusion parameters of moving molecules. In addition, we have investigated recent advances in dense motion estimation techniques and their potential for applications in live cell fluorescence imaging. We propose a novel diffusion estimation method in a variational framework providing dense and discontinuity-preserving diffusion fields. The performances of the variational and STICS approaches are evaluated in three representative biological studies. In particular, we demonstrate the accuracy of STICS in stationarity conditions, and we point out the advantages of dense variational estimation to accurately recover spatial and temporal discontinuities. Pre-processing steps and parameters influence are emphasized in the variational framework.