University of Rochester
Institute of OpticsPRAISE
Professor Fienup
Group members

Phase Retrieval and Imaging Science Group
Prof. James R. Fienup

The Phase Retrieval and Imaging Science Group in the Intitute of Optics at the University of Rochester performs research in the areas of unconventional imaging, phase retrieval, wave-front sensing, imaging with sparse-aperture telescopes, and image reconstruction algorithms.

What we do (paper titles analyzed by www.wordle.net)
(Click on the picture and enlarge the resulting window to get a magnified version of it:)

News Flashes:

Alex Iaccetta won a 2014 NASA Space Technology Research Fellowship (NSTRF14), for his proposal titled "Astro-Interferometric Modeling and Spatio-Spectral Reconstruction."

Matt Bergkoetter won the Synopsis 2013 Robert S. Hilbert Memorial Optical Design Competition. His project, "Extended Depth of Field in an Intrinsically Wavefront-Encoded Biometric Iris Camera" earned him a $1,000.00 prize. He is the fourth student in our group to win this prize, along with Matt Bolcar, Manuel Guizar-Sicairos and Dustin Moore.

Dustin Moore won the best student presentation award for a paper, "Wavefront Sensing by Phase and Modal Amplitude Retrieval," he gave at the Adaptive Optics topical meeting of the Optical Society of America in Arlington, VA, June 25, 2013.

Matt Bergkoetter, Alden Jurling and Dustin Moore were all selected as recipients of an NSF Travel Grants, paying for their travel expenses to the Imaging and Applied Optics Congress of the Optical Society of America.

Prof. Fienup won the OSA's Emmett Leith Medal and was elected to the National Academy of Engineering.

Recently Published Papers
(PDFs of these papers can be downloaded from our web site after clicking on the Publications box to the left.)

By Alden Jurling: “Phase retrieval with unknown sampling factors via the two-dimensional chirp z-transform,” J. Opt. Soc. Am. A 31, 1904-1911 (2014).

“Applications of Algorithmic Differentiation to Phase Retrieval Algorithms,” J. Opt. Soc. Am. A 31, 1348-1359 (2014).

“Extended Capture Range for Focus Diverse Phase Retrieval in Segmented Aperture Systems Using Geometrical Optics,” J.Opt. Soc. Am. A 31, 661-666 (2014).

By Prof. Fienup: “Phase Retrieval Algorithms: a Personal Tour [Invited],” Appl. Opt. 52, 45-56 (2013).

Examples of Research Problems

NASA's James Webb Space Telescope will need phase retrieval to align the 18 segments of the primary mirror. Similar phase retrieval algorithms were used to determine how to fix the Hubble Space Telescope.
NASA's Terrestrial Planet Finder and similar NASA missions will need phase-error correction for alignment of multiple (possibly flying-in-formation) interferometric imaging telescopes, and image reconstruction algorithms to undo image blurring due to sparse-aperture effects. We are currently applying these techniques to the problem of imaging geosynchronous satellites from the earth, despite atmospheric turbulence, and of wide-field infrared astronmical imaging.
Phase retrieval algorithms can be used to perform optical metrology, testing aspheric optical surfaces during their manufacture with a simple system not requiring a null lens. We are developing these ideas for measuring free-form optical surfaces.
Image sharpening algorithms can be used to estimate multiple phase screens throughout a volume of turbulence and reconstruct fine-resolution images of objects, despite the space-variant blurring effects of atmospheric turbulence.
Phase retrieval algorithms can be used to reconstruct fine-resolution images of satellites and astronomical objects, despite the blurring effects of atmospheric turbulence.
Telescopes having sparse apertures or are made up of an array of multiple smaller telescopes can give fine resolution images, while having large savings on size and weight. Image restoration and phase retrieval (to align the sub-apertures) are needed to achieve good quality imagery.