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Obtaining Superresolution with Super-Sampling
Event will begin: Tuesday, October 14, 2025 - 7:00 AM
Obtaining Superresolution with Super-Sampling
Presented by:
James Caron, QuarktetImage phase alignment super-sampling (ImPASS), a computational imaging algorithm for converting a sequence of displaced low-resolution images into a single high-resolution image, is applied for the first to sets of microscope images. This requires no customization to a standard widefield microscope other than a translation stage. Instead, high resolution information is obtained from Fourier phase information acquired by the alignment and combining of displaced frames.
Application of the self-deconvolving data restoration algorithm (SeDDaRA) blind deconvolution restores the higher spatial frequencies. Previous results demonstrated that the image resolution produced by this technique can subceed the diffraction limited resolution by as much as 2.6. 80-frame image sets had as targets a slide with a slice of porcine cornea, and a standard U.S. Air Force resolution chart, providing quantitative assessment. Resolution measurement revealed that image resolution improved by a factor of 2.68 and subceeded the diffraction limit by a factor of 1.79.
About the presenter
James N. Caron, Ph.D., is a research support contractor in the Washington, D.C., area. Recent projects include NASA/NOAA GOES-R series of geostationary weather satellites, Space Development Agency low-orbit optical communication network, and Naval Research Laboratory’s PUNCH series of Solar Coronagraphs.
Caron has developed an array of advanced image processing methods for real-world applications such as the SeDDaRA blind deconvolution method for non-iterative deblurring and Albedo Lunar Flattening for calibration of on-orbit cameras. He earned a bachelor’s in physics from Michigan State University and a doctorate in physics from the University of Delaware.
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