VILSS: Intelligent signal processing and learning in imaging

Panagiotis Tsakalides, University of Crete

Modern technologies, including the proliferation of high performance sensors and network connectivity, have revolutionized imaging systems used in applications ranging from medical and astronomical imaging to consumer photography. These applications demand even higher speed, scale, and resolution, which are typically limited by specific imaging and processing components. While striving for more complex and expensive hardware is one path, an alternative approach involves the intelligent design of architectures that capitalize on the advances in cutting edge signal processing to achieve these goals. This talk will motivate the need for smart integration of hardware components, on one hand, and software based recovery, on the other. The talk will showcase the benefits that stem from Compressed Sensing and Matrix Completion, two paradigm shifting frameworks in signal processing and learning, in two imaging problems, namely, range imaging and hyperspectral imaging. Challenges associated with properties of imaging data such as complexity and volume will also be presented and viewed under the prism of these algorithms.