Computational hybrid imaging reconstruction (Waller group)
Metrology – Computational Imaging
Computational imaging is an emerging field of metrology, involving the co-design of imaging system hardware and software for optimization across the entire pipeline from acquisition to reconstruction. The defining idea is that computers can replace bulky and expensive optics by solving computational inverse problems. With this approach, new, computational-imaging-based microscopes can be designed for 3D aberration and phase measurement. Computational imaging research in the BETR Center is led by Professor Laura Waller, and it is focused on designing imaging systems and algorithms jointly using simple hardware, which is easily adoptable and advanced image reconstruction algorithms based on large-scale optimization and learning. The Waller group is also exploring a new direction in computational imaging by not just reconstructing images from a given data set but encoding the information in the hardware and using data-driven approaches to optimize capture of the images and set up of the physical system in conjunction with image reconstruction. Past projects, for example, focused on a feasibility study for transferring optical phase measurements for inspection of large optical components in the supply chain of BETR Center industrial affiliate Lam Research. The team is also conducting fundamental research in the field of EUV lithography that could be applied to various semiconductor applications, including probing thin-film structures to sub-atomic length-scales, measuring phase of EUV masks for lithographic imaging, and investigating next-generation designs for EUV photomasks.