n this paper we compare correlation-based and variational approaches for both motion and diffusion estimation in fluo- rescence imaging. The so-called Spatio-Temporal Image Cor- relation Spectroscopy (STICS) is widely used in fluorescence imaging to recover physical parameters such as directional flow or diffusion parameters of moving molecules. In addi- tion, we have investigated recent advances in dense motion estimation techniques and their potential for applications in live cell fluorescence imaging. We propose a novel diffu- sion estimation method in a variational framework providing dense and discontinuity-preserving diffusion fields. The per- formances of the variational and STICS approaches are eval- uated in three representative biological studies. In particular, we demonstrate the accuracy of STICS in stationarity condi- tions, and we point out the advantages of dense variational estimation to accurately recover spatial and temporal discon- tinuities. Pre-processing steps and parameters influence are emphasized in the variational framework.