Computational imaging and illumination is an interdisciplinary approach that fuses together diverse fields such as optics, image processing, computer vision, and computer graphics, and plays a central role in a number of modern imaging techniques. The core idea is that captured images, rather than being a final product, are considered an intermediary to a final computed result. Some of the early work in this field was in computed tomography, coded aperture astronomy, and iterative phase retrieval algorithms developed in the latter part of the previous century. The past few decades have seen a significant increase in popularity of computational imaging methods at different physical scales, including a vast body of work in computational photography, as well as a significant achievements in computational microscopy, including the 2014 Nobel Prize in Chemistry for PALM/STORM.

In this talk, I will provide an overview of computational imaging technologies under development by the NU Comp Photo Lab, covering a large span of physical scales: from the nanoscopic to the astronomic. First, I will introduce a Synthetic Aperture Visual Imaging (SAVI) technique to image at high resolution over remote sensing scales (e.g. 100m-10km). SAVI uses camera arrays coupled with coherent illumination as an effective method of improving spatial resolution in long distance images by a factor of ten and beyond, essentially providing telescopic resolution using commodity hardware. Next, I will introduce a novel structured light technique designed to operate at macroscopic scales (e.g. 1-10m) called Motion Contrast 3D scanning (MC3D). MC3D maximizes bandwidth and light source power to avoid performance trade-offs in structured light 3D acquisition. The technique allows 3D laser scanning resolution with single- shot speed, even in the presence of strong ambient illumination, significant inter-reflections, and highly reflective surfaces. Lastly, I will present research on coherent diffraction imaging and tomographic reconstruction at the nanoscale, with applications to nanoscopic lensless X-Ray imaging. I will conclude with discussion and reflections on past, present, and future opportunities to bridge computational imaging approaches across a broad range of physical scales.

Oliver Cossairt is Assistant Professor in the Electrical Engineering and Computer Science Department at Northwestern University. Before joining Northwestern, he developed several key advances in 3D Display technology while earning my Masters at the MIT Media Lab and as an Optical Engineer at Actuality Systems, resulting in 8 patents. He earned his Ph.D. from Columbia University, where he was awarded an NSF Graduate Research Fellowship for his thesis work on the theoretical limits of computational imaging. Prof. Cossairt is currently director of the Computational Photography Laboratory at Northwestern University, whose research consists of a diverse portfolio, ranging in topics from optics/photonics, computer graphics, computer vision, and image processing. He has written a number of high-impact publications including ACM SIGGRAPH, IEEE Pattern Analysis and Machine Intelligence, and IEEE Transaction on Image Processing, and received Best Paper (2011) and Honorable Mention (2014) awards for publications at the IEEE International Conference on Computational Photography. He has given a keynote talk at the IEEE Computational Cameras and Displays Workshop (2013), as well as invited talks at a number of conferences including: AAAS (2015), COSI (2013,2015,2016), CLEO Europe (2015), ICIP (2015, 2016), IPAM Computational Photography (2015), and FRINGE (2013). He has co-organized several workshops, serves on 5 conference program committees annually, and as Associate Editor for the IEEE Transactions on Computational Imaging. In the Spring of 2016, He co-organized the International Conference on Computational Photography (ICCP), held at Northwestern University. His research projects have garnered funding from numerous corporate sponsorships (Google, Rambus, Samsung, Omron, Oculus) and federal funding agencies (ONR, NIH, DOE, NSF CAREER Award, DARPA, IARPA).

Researchers should cite this work as follows:

• Oliver S. Cossairt (2017), "Computational Imaging From Nanoscopic to Astronomical Scales," https://nanohub.org/resources/26775.

  BibTex | EndNote

1. computational imaging
2. Imaging
3. motion contrast 3D scanning
4. syntehetic aperture