ITACTIC - Infrared Target Acquisition, Classification, and Tracking via Image Compression

InView Technology Corporation and its partner Rice University propose the simulation, analysis, development and demonstration of a novel infrared imaging system that provides enhanced compressive sensing-based target detection, classification and tracking capabilities where all processing and reasoning techniques are performed directly in the measurement domain, without the expense of sparsity-based signal reconstruction. Performing signal processing directly in the sparse measurement domain has several advantages including the elimination of signal reconstruction time and processing costs and a reduction in the volume of raw data that limits computational and communication throughput. In computer vision applications not only is there no need to reconstruct signals or images, but autonomous machine learning can proceed with higher efficiency in lower dimensional spaces.In Phase I, feasibility and robustness of such an approach was demonstrated using simulation and further evaluated the performance of various the computationally-based optical approaches to performing compressive sensing-based target detection directly in the compressed domain on a short-wave image target library.The objective of Phase II is to expand, optimize and benchmark these mathematical techniques and implement them on an operational infrared compressive sensing hardware platform both in the laboratory and the field.