Non-imaging advanced scene characterization
Abstract
It is intuitive that, in the problem of estimating the separation of two-point sources, the closer the sources become, the more difficult the task. This limitation is intimately related to the study of resolution. The term superresolution refers to a variety of concepts that allow for the determination of two-point source separations that are separated by distances that are less than allowed by the direct imaging incoherent resolution limit A specific area that has received much recent attention are superresolution approaches based on local spatial frequencies that exceed the system’s bandlimit – so called superoscillations. Although superoscillations provide a pathway to better resolution, the enhanced resolution comes with a drawback – it suffers from extremely low light levels. Considering the resolvability benefits with superoscillations, one is left to wonder – might there exist approaches that offer resolution benefits with a larger signal-to-noise ratio? The proposed program will explore two non-imaging approaches to superresolution that promise to resolve the separation of two unequal amplitude point sources at separations that are below the diffraction limit. The first approach is based on the recent discovery by the PIs that large local spatial frequency content can exist in regions where the optical energy is not negligible. These locations of supergrowth can lead to sub-diffraction limited scene characterization utilizing intensity contrast measurements. The second approach is based on making projective measurements of the received optical energy in an appropriate set of spatial modes. Theories will be developed, based on the Fisher information and Cramer-Rao bound, to understand the maximum information that can be distilled from a scene using these techniques and theory will be complemented with the first proof-of-principle experimental confirmations.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 21, 2022
- Source ID
- FA95502110322XX0
Entities
People
- Anthony Vamivakas
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Rochester