Information and Image Fusion seeks to combine heterogeneous information (sensor signals, data, text, image, etc.) from multiple sources to achieve inferences that are not feasible from a single source.

The proliferation of micro and nano-scale sensors, wireless communication, and ubiquitous computing enables the assembly of information from sensors, models, and human input for a wide variety of applications such as extreme events monitoring, crisis management, risk assessment, and social network analysis. Techniques for information and image fusion are drawn from statistical estimation, signal processing, image analysis, artificial intelligence, and the information sciences.

Major issues involve architectures for distributed sensing and processing, selection and integration of fusion algorithms, visualization of fusion results, allocation of sensor resources based on market principles and hypotheses, and content-based image analysis.