Points of Lights
Don't Blink Or You Might Miss The Next Big (Quantum) Thing
By Deborah Wormser
Christensen says SMU’s photonics researchers – who include
faculty members in electrical engineering, mathematics and
physics, plus their graduate students – come together periodically
for interdisciplinary meetings because so many fields are involved
in creating and understanding photonic devices.
Christensen’s Photonic Architectures Laboratory has received
more than $2 million in grants from the Defense Advanced Research
Projects Agency (DARPA) for a project to make unmanned
aerial vehicles (UAVs) stealthier “Today we think of a Predator UAV as flying at 30,000 feet carrying
a really nice camera with a long lens that can zoom into an area on the ground and look at it very carefully,” he says. Ideally, the device
would be tiny with a flat lens, like a cell phone camera; however,
those cameras do not produce images of adequate resolution.
Christensen’s interdisciplinary team has devised a multi-step solution
that starts with an array of hundreds of tiny, flat, square
cameras and equally tiny, square mirrors placed in a grid pattern
that can be mounted on the underside of an aircraft as small as a
model airplane. Each camera will provide slightly different information
about the subject because each takes a photograph from a
slightly different angle. Computational imaging is then used to
combine the numerous low-resolution images to create a sharper
image that is akin to one taken by a high-performance camera too
heavy to fit on the small aircraft.
“Wouldn’t it be great if the camera could determine from its
wide shot which objects in the field are most important and be
able to zero in on them?” Christensen asks.
Such a camera is under development at SMU. Called an adaptive
resolution camera, it would analyze the wide view and use
mathematical formulas to identify objects of interest – such as
aircraft on the ground.
Instead of simple mirrors, the adaptive resolution camera uses
an array of micro-electric machines (MEMs). Each MEM looks
like a mirror that is hundreds of microns across, or about the width
of a few human hairs, attached to three even smaller levers. The
levers would reposition the mirrors in the desired direction to improve
the information collected by the camera’s next photographs
to create another, better image – all faster than the blink of an eye.
The smarter camera would automatically put more pixels in the
areas of interest and less in those considered unimportant, he says,
adding that the resulting picture may look strange by conventional
standards, but it would provide more useful information.
The team from the Electrical Engineering Department incorporates
skills from physics, mathematics and computer science.
Assistant Professor Dinesh Rajan, a specialist in information theory,
finds the mathematical route to the best final image, a so-called
“goodness value.” Associate Professor Scott Douglas, an adaptive algorithms expert, crafts the formulas to make the system home in
on the important details within the big picture. And Professor Panos
Papamichalis works on their robustness, making the system more
tolerant of the adversities the camera will encounter in daily use.