RI: Small: Time Resolved Imaging: New Methods for Capture, Analysis and Applications

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This project fundamentally combines the emerging time of flight imaging techniques with computational methods to redefine a camera and also go beyond the conventional barriers in scientific imaging. Imaging has transformed science and technology in many fields. Time-aware ultrafast imaging can bring further radical new innovations in coming years. Recently, there has been a significant commercial interest in converting time-aware sensors into low cost consumer solutions. Going forward, solving time-based forward and inverse transport problems can impact new fundamental research in biology, physics, optics, computer science, engineering, and mathematics, with broad applications in health, robotics, defense, and mobility. They have high potential to stimulate economic investment and entrepreneurship using modern imaging solutions. Emerging image sensors with picosecond (ps) time resolution provide new ways to capture and understand the world. For scene analysis, typical computational imaging techniques exploit sensor parameters such as spatial resolution, wavelength, and polarization. However, they are far slower than light speed and are consequently limited in their ability to model the complex dynamics of light propagation. Time-resolved (or transient) sensors overcome this limitation, but their integration with computational methods has not been realized yet. Therefore, with the recent spurt in commercial time-of-flight (ToF) systems, new research in transient computational imaging is well-timed. Beyond ToF depth information, this research explores the capture and analysis of per-pixel time profiles at ps scales. This leads to joint re-examination of fundamental inverse problems and solutions in scientific, industrial and consumer applications. Specifically the project builds computer vision algorithms for seeing objects beyond the line of sight, behind diffusive layers and inside turbid media. This provides novel applications in medical imaging. With the development of the theoretical foundation and enabling tools, the project accelerates research and commercialization of this new field.