RI: Small: New Optical Frontiers for 4D Computational Imaging Systems

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Imaging is a core technology that feeds into intelligent sensing and reasoning about the world. This project advances the frontiers of imaging by supporting development of a broad, new space of "4D lens" designs with fundamentally superior performance. The research team develops technologies to record and process richer data about light flowing through the lens, enabling computational enhancement over the optical image quality. The research team also redesigns the lens itself, lowering the optical requirements and pushing to unprecedented performance in figures of merit such as brightness, size, weight, zoom and cost. This project extends the frontier of what is possible in diverse imaging applications, including 3D imaging, photography, scientific imaging, projection, lithography, and headsets for virtual and augmented reality, microscopy, security and defense. This research develops the theory, algorithms and tools for designing and optimizing the described 4D lenses. The enabling technical shift is the assumption that the new lenses can be used in the emerging class of computational imaging systems that work with the full 4D light field (set of all rays), rather than simply a 2D image. This project addresses several intellectual challenges theoretically and algorithmically. First, the research establishes a new formulation of the long-standing lens design problem, considering not just 2D optical image quality, but rather the computed image quality after end-to-end 4D imaging and processing. The new formulation significantly increases the complexity of evaluating and optimizing lens designs. Secondly, the research explores and maps the new frontier of lens design space that this approach opens up, to understand its growth characteristics and ultimate limits. The new design approach has potential for fundamental disruption of imaging capability, because it enables lens technology to improve continuously with technology for pixels and processing, which grow exponentially.