An Intelligent and Adaptive Class-Based Compression Technology for Weapon Seekers Suitable for Minimum RF Bandwidth

The quality and quantity of information directly available to command authorities is becoming an increasingly dominant factor in modern force projection. The increasing demand for information of digital imagery and real time video has exposed the severe bandwidth limitation of RF data link resources. This limitation becomes more severe as the future smart weapons will be integrated into warfighting networks. To minimize RF bandwidth requirement (and thus minimize cost), the solution is to intelligently and adaptively compress the data without destroying too much critical detail. Current Data-driven compression schemes do not have the capabilities to take advantage of recognizable conceptual primitive patterns such as edges, corners, strips, which can be modeled by strongly adaptive intelligence based schemes using machine-intelligence. For significant compression improvements, a paradigm shift to a pattern-driven approach is required whereby images are considered as relational entities, classifiable according to the presence of patterns, their relationships and their frequency of occurrence. UC technology will offer real-time image/video codec with a 400% improvement in compression performance compared to current codecs. The objective of this proposal is to develop a class-based codec with embedded security offering substantial reduction in volumes of rich content for real-time RF communication of mission-critical applications.