Metalens for Full-Color Imaging

A metalens consists of arrays of tiny pillars of silicon nitride on glass which affect how light interacts with the surface. A traditional metalens (top) exhibits shifts in focal length for different wavelengths of light, producing images with severe color blur. The modified metalens design (bottom), however, interacts with different wavelengths in the same manner, generating uniformly blurry images which enable simple and fast software correction to recover sharp and in-focus images. (Source: S. Colburn, A. Zhan, A. Majumdar)

For photo­graphers and scientists, lenses are lifesavers. They reflect and refract light, making possible the imaging systems that drive discovery through the micro­scope and preserve history through cameras. But today’s glass-based lenses are bulky and resist minia­turization. Next-genera­tion techno­logies, such as ultrathin cameras or tiny micro­scopes, require lenses made of a new array of materials. Scientists at the Univer­sity of Washing­ton announced now that they have success­fully combined two different imaging methods: a type of lens designed for nanoscale inter­action with light­waves, along with robust compu­tational processing to create full-color images.

The team’s ultrathin lens is part of a class of meta­surfaces. A meta­surface-based lens consists of flat micro­scopically patterned material surfaces designed to interact with lightwaves. To date, images taken with meta­lenses yield clear images at best for only small slices of the visual spectrum. But the UW team’s metalens in conjunc­tion with compu­tational filtering yields full-color images with very low levels of aber­rations across the visual spectrum. “Our approach combines the best aspects of meta­lenses with compu­tational imaging – enabling us, for the first time, to produce full-color images with high effi­ciency,” said Arka Majumdar, a UW assistant professor of physics and electrical engi­neering.

Instead of manu­factured glass or silicone, meta­lenses consist of repeated arrays of nano­meter-scale structures, such as columns or fins. If properly laid out at these minuscule scales, these structures can interact with indi­vidual lightwaves with precision that tradi­tional lenses cannot. Since meta­lenses are also so small and thin, they take up much less room than the bulky lenses of cameras and high-reso­lution micro­scopes. Metalenses are manu­factured by the same type of semi­conductor fabri­cation process that is used to make computer chips. “Metalenses are poten­tially valuable tools in optical imaging since they can be designed and con­structed to perform well for a given wave­length of light,” said Shane Colburn, a UW doctoral student in electrical engi­neering. “But that has also been their drawback: Each type of metalens only works best within a narrow wave­length range.”

Today’s meta­lenses typi­cally produce accurate images within their narrow optimal range – such as an all-green image or an all-red image. For scenes that include colors outside of that optimal range, the images appear blurry, with poor reso­lution and chromatic aber­rations. For a rose in a blue vase, a red-opti­mized metalens might pick up the rose’s red petals with few aber­rations, but the green stem and blue vase would be unre­solved blotches with high levels of chromatic aber­rations. Majumdar and his team hypo­thesized that, if a single metalens could produce a consistent type of visual aber­ration in an image across all visible wave­lengths, then they could resolve the aber­rations for all wave­lengths afterward using compu­tational fil­tering algo­rithms. For the rose in the blue vase, this type of meta­lens would capture an image of the red rose, blue vase and green stem all with similar types of chromatic aber­rations, which could be tackled later using compu­tational fil­tering.

The metalens, coupled with computational processing, can capture images for a variety of light wavelengths with very low levels of chromatic aberrations. For this black-and-white image of the Mona Lisa (at top), the first row shows how well a green-optimized metalens captures the image for green light, but causes severe blurring for blue and red wavelengths. The UW team’s improved metalens (second row) captures images with similar types of aberrations for blue, green and red wavelengths, showing uniform blurring across wavelengths. But computational filtering removes most of these aberrations, as shown in the bottom row, which is a substantial improvement over a traditional metalens (first row), which is only in focus for green light and is unintelligible for blue and red. (Source: S. Colburn, A. Zhan, A. Majumdar)

They engi­neered and constructed a meta­lens whose surface was covered by tiny, nano­meters-wide columns of silicon nitride. These columns were small enough to diffract light across the entire visual spectrum, which encom­passes wave­lengths ranging from 400 to 700 nano­meters. Criti­cally, the researchers designed the arrange­ment and size of the silicon nitride columns in the metalens so that it would exhibit a spectrally inva­riant point spread function. Essen­tially, this feature ensures that for the entire visual spectrum the image would contain aber­rations that can be described by the same type of mathe­matical formula. Since this formula would be the same regard­less of the wave­length of light, the researchers could apply the same type of compu­tational processing to correct the aber­rations.

They then built a proto­type metalens based on their design and tested how well the metalens performed when coupled with compu­tational processing. One standard measure of image quality is structural simi­larity – a metric that describes how well two images of the same scene share lumi­nosity, structure and contrast. The higher the chromatic aber­rations in one image, the lower the structural simi­larity it will have with the other image. The UW team found that when they used a conven­tional metalens, they achieved a structural simi­larity of 74.8 percent when comparing red and blue images of the same pattern; however, when using their new metalens design and compu­tational proces­sing, the structural simi­larity rose to 95.6 percent. Yet the total thickness of their imaging system is 200 micro­meters, which is about 2,000 times thinner than current cellphone cameras.

“This is a substan­tial improve­ment in metalens performance for full-color imaging parti­cularly for elimi­nating chromatic aber­rations,” said Alan Zhan, a UW doctoral student in physics. In addition, unlike many other meta­surface-based imaging systems, the UW team’s approach isn’t affected by the polari­zation state of light which refers to the orien­tation of the electric field in the 3-D space that light­waves are traveling in. The team said that its method should serve as a road map toward making a metalens and designing addi­tional compu­tational processing steps that can capture light more effectively, as well as sharpen contrast and improve reso­lution. That may bring tiny, next-genera­tion imaging systems within reach. (Source: UW)

Reference: S. Colburg et al.: Metasurface optics for full-color computational imaging, Science 4, eaar2114 (2018); DOI: 10.1126/sciadv.aar2114

Link: Dept. of Electrical Engineering, Univ. of Washington, Seattle, USA

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