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He shows me a regular black-and-white image of the painting, a blurred black-and-white form indicating the jumble of spirals the sensor would capture for the computer to interpret, and a blurry but still recognizable black-and-white image of the painting as reconstructed from this data by software. Gill uses the Mona Lisa image to demonstrate.

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The sensor below the grating captures a jumble of spirals that a human wouldn’t see as a recognizable image, but software can translate into one. Rambus’s approach instead uses a grating etched with a spiral pattern through which light can enter from every orientation. When you take a picture of a painting on a wall with a regular digital camera, a lens focuses each point of light it captures on a sensor, generating a digital file that a computer can show you as an image. A tiny segment of the chip contains a spiral that has been used to capture a number of images, including the Mona Lisa picture Gill shows me as well as fuzzy depictions of John Lennon and Georges Seurat’s Bathers at Asnières. Gill shows me a prototype sensor at Rambus’s Sunnyvale office that has been etched with 28 different types of diffractive structures-spirals and other shapes like a cross and a pentagon. The middle image is the computer’s reconstruction it’s fuzzier than the original (bottom image) but still recognizable. The top image shows what the sensor captures.

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