Sampling the parameter domain of image series

While analyzing a scene of interest in real environments, the acquisition and evaluation of image series has proven to yield promising results in providing useful information. However, acquiring and evaluating image series imposes several difficulties on the imaging and analysis process: The amount of data to be processed increases significantly, especially when more than one parameter is varied. Recording image series thus leads to a dilemma: Whereas a dense scanning of the varied parameter is desirable in order not to lose any information of interest, the number of recorded images should be as small as possible to ensure both adequate acquisition time and manageable amount of data. This dilemma can be considered as a sampling issue of the parameter spaces of a variable image acquisition. In this contribution, the topic of optimally sampling the parameter spaces for image series is addressed from a practical point of view. Sampling conditions for several parameters to be varied are derived from physics and image formation models