Visualization of scientific video data using KL decomposition

Fast methods are developed for visualizing and classifying certain types of scientific video data. These techniques, which are based on Karhunen-Loe`ve (KL) decomposition, find a best coordinate system for a data set. When the data set represents a temporally ordered collection of images, the best coordinate system leads to approximations that are separable in time and space. Practical methods for computing this best coordinate system are discussed, and physically significant visualizations for experimental video data are developed. The visualization techniques are applied to two experimental systems-one from combustion and the other from neurobiology-to show how relevant information can be quickly extracted from video data. These techniques can be integrated into the video acquisition process to provide real-time feedback to the experimentalist during the operation of an experiment