We present an alternative approach for using dynamic laser speckle data to quantify biophysical dynamics including ordered flows and random motions. The approach yields images that superficially resemble traditional laser speckle contrast images, but instead of relying on the statistics of the local time integrated intensity values calculated over temporal and sliding spatial windows as is done in LSCI to create images, ellipticity imaging (EI) directly yields images that quantify the relative dominance of long-range correlations in the temporal dimension of a series of speckle patterns to the short-range correlations in the same dimension. The approach relies on a Poincaré analysis of the speckle data which yields metrics that statistically describe both the short-terms variations in the temporal speckle intensity (i.e., the standard deviation in successive differences) and also the corresponding long term variations. These metrics are plotted against each other (Poincaré plots) and an ellipse fit to the data. The ratio of the semi-major axis to the semi-minor axis of this ellipse for each temporal speckle sequence is then used as the data to form the images (thus the term EI). The results of flow phantom and mouse EI studies will be presented. Various flow rates of dilute intralipid were illuminated with a coherent laser source and EI images were generated. The same speckle data were analyzed using spatial and temporal LSCI approaches. Flows in anesthetized mouse brain vessels were analyzed using EI and LSCI approaches. The results of the studies using the different speckle analyses will be discussed.