Abstract

This talk will review the framework of compressive sensing, spotlighting its implementation in optical imaging and spectroscopy systems. The basis of these systems is a well-established body of work which asserts that one can exploit sparsity or compressibility when acquiring signals of general interest, and that one can design nonadaptive sampling techniques that condense the information in a compressible signal using far fewer data points than were thought necessary. Comparisons between various system designs and specific implementations will be discussed. Examples will include implementation in infrared, hyperspectral, and terahertz imaging systems. The implementation of model-based imaging strategies will also be discussed. Article not available.

© 2011 Optical Society of America