“Compressed sensing is an exciting new computational technique for extracting large amounts of information from a signal. In one high-profile demonstration, for instance, researchers at Rice University built a camera that could produce 2-D images using only a single light sensor rather than the millions of light sensors found in a commodity camera. But using compressed sensing for image acquisition is inefficient: That “single-pixel camera” needed thousands of exposures to produce a reasonably clear image. Reporting their results in the journal IEEE Transactions on Computational Imaging, researchers from the MIT Media Lab now describe a new technique that makes image acquisition using compressed sensing 50 times as efficient. In the case of the single-pixel camera, it could get the number of exposures down from thousands to dozens. One intriguing aspect of compressed-sensing imaging systems is that, unlike conventional cameras, they don’t require lenses. That could make them useful in harsh environments or in applications that use wavelengths of light outside the visible spectrum. Getting rid of the lens opens new prospects for the design of imaging systems.”