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New Technique Retrieves Color Images from Scattered Light

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DURHAM, N.C., July 30, 2019 — Engineers at Duke University have developed a method for extracting a color image from a single exposure of light scattered through a mostly opaque material. The new approach overcomes the limitations of conventional optical memory effect techniques in the realm of color, by using spectral coding and compressed sensing to achieve snapshot color imaging through scattering media.

The Duke team realized multispectral imaging of objects through scattering media using only a single speckle measurement with a monochrome camera. The researchers used a coded aperture in combination with a wavelength-dependent element, such as a prism, to encode the spectral content within the low-contrast, multiplexed speckle signal. Then they used a compressed sensing algorithm to recover the speckle signals associated with each independent spectral channel, which were then processed using correlation-based algorithms.

Recovering color images from scattered light, Duke University.

Researchers have created a method that takes light from colored numerals (top left) that has been scattered by a mostly opaque surface (top center) and uses its speckle patterns and a coded aperture to reconstruct the image in five different frequencies (bottom row) before combining them into a final image (top right). Courtesy of Michael Gehm, Duke University.

As the speckle passed through the prism, different frequencies of light spread out from each other, causing the pattern from the coded aperture to shift slightly in relation to the image being captured. The amount that the pattern shifted was directly related to the color of light passing through.

“This shift is small compared to the overall size of what’s being imaged, and because our detector is not sensitive to color, it creates a messy combination,” researcher Xiaohan Li said. “But the shift is enough to give our algorithm a toehold to tease the individual speckle patterns apart from each color, and from that we can figure out what the object looks like for each color.”

The researchers produced high-fidelity images of a target object at five well-separated spectral channels between 450 nm and 750 nm. They also demonstrated experimental imaging of three well-separated spectral channels between 450 nm and 650 nm and six contiguous spectral channels between 515 nm and 575 nm. They showed that by focusing on five spectral channels corresponding to violet, green, and three shades of red, their technique could reconstruct a letter “H” full of nuanced pinks, yellows, and blues. 

The researchers believe their approach could find applications in the fields of astronomy and health care. “There are a lot of applications where people really want to know how much energy there is in specific spectral bands emitted from objects located behind opaque occlusions,” professor Joel Greenberg said. “We’ve shown that this approach can accomplish this goal across the visible spectrum. Knowing the aperture pattern and how much it shifts as a function of wavelength provides the key we need to disentangle the messy sum into separate channels.”

In astronomy, the color content of the light coming from astronomical phenomena contains valuable information about its chemical composition, and speckle is often created as light is distorted by the atmosphere. Similarly in health care, color can tell researchers something about the molecular composition of what’s being imaged, or it can be used to identify biomolecules that have been tagged with fluorescent markers.

“Others have been able to reconstruct color images from scattered light, but those methods had to sacrifice spatial resolution or required prior characterization of the scatterer in advance, which frequently isn’t possible,” professor Michael Gehm said. “Our approach avoids all those issues.”

The research was published in Optica, a publication of OSA, The Optical Society (https://doi.org/10.1364/OPTICA.6.000864). 

Photonics.com
Jul 2019
GLOSSARY
multispectral imaging
Multispectral Imaging: Creation of an image where each pixel contains more than three spectral data points, typically four to 20. This is contrasted with a standard color camera that only captures three spectral data points (called RGB), or hyperspectral cameras, which capture hundreds of spectral data points. Traditional multispectral cameras captured four data points: RGB and an NIR band. Nowadays multispectral cameras are available as commercial off-the-shelf products, with 12 custom bands...
astronomy
The scientific observation of celestial radiation that has reached the vicinity of Earth, and the interpretation of these observations to determine the characteristics of the extraterrestrial bodies and phenomena that have emitted the radiation.
Research & TechnologyeducationAmericasDuke Universityimaginglight sourcesopticsSensors & DetectorscamerasPrismsFiltersmultispectral imagingscattered lightspeckle patternshealth careastronomymedicalBiophotonicsoptical memory effect

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