This report describes the results of a two-year Phase II STTR program undertaken by InView in partnership with Rice University to develop a compressive sensing based imager with high speed anomaly detection capability. During this period, novel multi-channel compressive sensing measurement patterns and detector geometries were developed along with statistical methods for performing anomaly detection on data in the compressed domain. Detection performance was analyzed using receiver operating characteristic and precision recall curves. New concepts, algorithms and techniques were simulated and tested experimentally using specially modified compressive sensing cameras under laboratory conditions. It was found that the number of measurements needed for anomaly detection was far less than the number of measurements needed for compressive imaging, validating high speed system operation.