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New data compression method reduces big-data bottleneck; outperforms, enhances JPEG

In creating an entirely new way to compress data, a team of researchers from the UCLA Henry Samueli School of Engineering and Applied Science has drawn inspiration from physics and the arts. The result is a new data compression method that outperforms existing techniques, such as JPEG for images, and that could eventually be adopted for medical, scientific and video streaming applications.

In data communication, scientific research and medicine, an increasing number of today’s applications require the capture and analysis of massive amounts of data in real time.

But “big data,” as it’s known, can present big problems, particularly in specialized fields in which the events being studied occur at rates that are too fast to be sampled and converted into digital data in real time. For example, in order to detect rare cancer cells in blood, researchers must screen millions of cells in a high-speed flow stream.

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