Algorithm reconstructs hyperspectral images with less data

According to NC State, the images are created using instruments that capture hyperspectral information succinctly, and the combination of algorithm and hardware makes it possible to acquire hyperspectral images in less time and to store those images using less memory.

Hyperspectral imaging is said to hold promise for use in fields ranging from security and defence to environmental monitoring and agriculture.

Conventional imaging techniques, such as digital photography, capture images across three wavelengths – frequencies – of light, from blue to green to red, whereas hyperspectral imaging creates images across dozens or hundreds of wavelengths. These images can be used to determine the materials found in whatever scene was imaged.

However, in a conventional imaging system, if an image has millions of pixels across three wavelengths, the image file might be one megabyte. But in hyperspectral imaging, the image file could be at least an order of magnitude larger, creating problems for storing and transmitting data.