Image analysts can see the avalanche coming. A mountain of satellite imagery is growing faster than the rate at which they can turn data into useful pictures, such as a Google map.

Rochester Institute of Technology graduate student Abdul Haleem Syed ’08 (B.S., electrical engineering) is working to prevent imagery overload.

“Two hundred-eighty Earth observation satellites will be launched this decade compared to 135 launched in the previous decade,” says Syed, from Hyderabad, India. “That is a lot of images of Earth being collected but someone—usually an image analyst—has to manually work with these images to extract important information.”

Efficiently extracting useful bits of information from an image of a larger scene is at the heart of Syed’s doctoral research at RIT’s Chester F. Carlson Center for Imaging Science. He presented his novel research methods at the International Conference on Geographical Object-based Image Analysis May 7­–9 in Rio de Janeiro, Brazil, where he won best student paper for “Encoding of Topological Information in Multi-scale Remotely Sensed Data: Applications to Segmentation and Object-based Image Analysis.”

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