To address the Air Force need for advanced compression algorithms for exploitation of space imagery, Physical Optics Corporation (POC) proposes to develop a new Advanced Region of Interest (ROI) Foveation Catastrophe-based Compression (ARIFCaC) software suite. It is based on new ROI foveation, POCs Catastrophe-theory-based algorithmic software, and POCs advanced lossless and lossy (but perceptually lossless) compression algorithm. The innovations in ARIFCaC, including ROI foveation, Catastrophe-theory-based structural information encoding, and synergistic perceptually lossless compression, will enable the software suite to improve detection capability, metric accuracy, and tracking and estimation of fast-evolving scenarios. As a result, this technology offers processor- and bandwidth-efficient compression and image exploitation algorithms for the Air Forces future space surveillance applications, which directly address the requirements of Space-Based Space Surveillance (SSBS) programs, specifically the SBSS Pathfinder satellite program. In Phase I, POC will demonstrate the feasibility of ARIFCaC by providing quantified improvements in compression ratio and image exploitation processes using training data sets provided by the Air Force. In Phase II, POC plans to demonstrate the optimized ARIFCaC software suite, which minimizes computational burden but maximizes compression ratios, as well as detection capability and tracking ability of objects on the test data provided.
Benefit: Since the ARIFCaC provides perceptually lossless compression and advanced image exploitation, it can be used in medical imaging applications, which have very strict parameters and do not allow compression because it will lose details in the image. It will not only save transmission time, but also storage requirements and infrastructure costs. The technology will provide the same benefits to the security and surveillance areas, as well to current information-rich applications. Classical problems in space surveillance are limited processing time and available downlink bandwidth. With the ARIFCaC technology, these classical problems in remote sensing, deep space surveillance, and target tracking applications can be greatly alleviated.
Keywords: Catastrophe Theory, Region Of Interest, Target Tracking, Target Detection, Lossless Compression, Perceptually Lossless Compression, Space Based Space Surveillance, Space-Based
