Flat optics for image differentiation

You Zhou, Hanyu Zheng, Ivan I. Kravchenko, Jason Valentine

Research output: Contribution to journalArticlepeer-review

411 Scopus citations

Abstract

Image processing has become a critical technology in a variety of science and engineering disciplines. Although most image processing is performed digitally, optical analog processing has the advantages of being low-power and high-speed, but it requires a large volume. Here, we demonstrate flat optics for direct image differentiation, allowing us to significantly shrink the required optical system size. We first demonstrate how the differentiator can be combined with traditional imaging systems such as a commercial optical microscope and camera sensor for edge detection with a numerical aperture up to 0.32. We next demonstrate how the entire processing system can be realized as a monolithic compound flat optic by integrating the differentiator with a metalens. The compound nanophotonic system manifests the advantage of thin form factor as well as the ability to implement complex transfer functions, and could open new opportunities in applications such as biological imaging and computer vision.

Original languageEnglish
Pages (from-to)316-323
Number of pages8
JournalNature Photonics
Volume14
Issue number5
DOIs
StatePublished - May 1 2020

Funding

We acknowledge support from the Office of Naval Research under award no. N00014-18-1-2563 and DARPA under the NLM programme, award no. HR001118C0015. Part of the fabrication process was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility. The remainder of the fabrication process took place in the Vanderbilt Institute of Nanoscale Science and Engineering (VINSE) and we thank the staff, particularly K. Heinrich, for their support.

Fingerprint

Dive into the research topics of 'Flat optics for image differentiation'. Together they form a unique fingerprint.

Cite this