Image Science

Image science investigates the ways that image quality can be defined, measured and optimized; it touches and improves the visualization of everything from healthy bones to unstable atmospheres to millennia-old geological formations. This interdisciplinary field studies the physics of photon generation, the propagation of light through optical systems, signal generation in detectors and more, and considers the statistics of random processes and how they affect the information contained within images.

The faculty in image science at the Wyant College of Optical Sciences show particular strength in designing new technology for medical imaging, homeland security, earth sciences and other applications, and in developing new methods for assessing image quality by quantifying how accurately imaging systems can accomplish certain analytical tasks.

To view past updates, see the Research Updates Archive.

conceptual design of a quantum-optimal direct-imaging coronagraph

1) Searching for the Perfect Coronagraph to Find Another Earth

In the lab of Amit Ashok, professor of optical sciences, researchers are pushing the boundaries of exoplanet discovery with quantum optics. In a new study, the team investigates whether current coronagraph designs—devices used to block out light from a star in order to see orbiting planets—are the best possible tools for finding and characterizing exoplanets. The team goes into detail on the project in the publication, "Achieving Quantum Limits of Exoplanet Detection and Localization." By applying quantum information techniques, they found that ideal coronagraphs, which eliminate only specific optical modes, may offer a significant improvement in detecting and localizing exoplanets, even for tightly-orbiting exoplanets residing below the diffraction limit of the telescope. This research could pave the way for more effective methods to study Earth-like exoplanets and expand our understanding of planetary systems.

Journal Covers from Student Publications

2) Optical Sciences Students’ Research Featured on Covers of Journals Showcasing Impactful Work in Biomedical Research

Three Wyant College of Optical Sciences PhD students, all advised by Travis Sawyer, Assistant Professor of Optical Sciences, have had their research featured on prominent journals' covers. Justina Bonaventura is first author of the article, "Evaluating backscattering polarized light imaging microstructural mapping capabilities through neural tissue and analogous phantom imaging," published in the May 2024 issue of SPIE's peer-reviewed Journal of Biomedical Optics. Noelle Daigle and Shuyuan Guan; with advisor, Travis Sawyer; co-authored the article, "Two-Photon Microscopy Provides Clear Guidance for Tumor Resection," featured in the May/June 2024 issue of BioPhotonics, a news journal published by Photonics Spectra.

Football game imaged with a gigapixel camera, with zoomed in details. Image resolution is uniform across the scene

3) Next-gen imaging takes pictures that speak a million pixels: Growth of computational imaging could drive it beyond the limits of optical systems

Professor David Brady's work in computational imaging attracted the attention of writers at SPIE who focused an article on the work he is doing to build a camera capable of creating the world's first gigapixel images. The machine contains an array of 98 microcameras with microprocessors that can stitch the individual images together. According to the article, "Computational imaging, on the other hand, allows users to refocus a photo, construct a 3D picture, combine wavelengths, or stitch together separate images into one.

Comparing the reconstruction results with different aperture distributions. The full resolution images were reconstructed but only the zoomed-in details of the reconstructed images are shown for easy comparison.

4) Snapshot ptychography on array cameras

A new paper in Optics Express Vol. 30, Issue 2 features the work of Chengyu Wang, Minghao Hu, Yuzuru Takashima, Timothy J. Schulz, and David J. Brady. The team uses convolutional neural networks to recover images optically down-sampled by 6.7 × using coherent aperture synthesis over a 16 camera array. Where conventional ptychography relies on scanning and oversampling, here the researchers apply decompressive neural estimation to recover full resolution image from a single snapshot, although as shown in simulation multiple snapshots can be used to improve signal-to-noise ratio (SNR).

5) Smartphone Confocal Microscopy for Imaging Cellular Structures in Human Skin in Vivo

Using a slip aperature and diffraction grating on a smartphone, the research team, including Dongkyun "DK" Kang, has developed a confocal microscope. It's use for in vivo human skin imaging was successful, conducting two-dimensional confocal imaging without the need for any beam scanning devices. These results suggest that the smartphone confocal microscope has a potential to be a low-cost option capable of examining cellular details in vivo and may help disease diagnosis in resource-poor settings, where conducting standard histopathological analysis is challenging.