Applied Physics

Compressively Sensing Ghosts

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Science  05 Jul 2013:
Vol. 341, Issue 6141, pp. 11
DOI: 10.1126/science.341.6141.11-d

The storing and processing of images can place large overheads on the hardware and software required to identify targets within each frame. Compressive sensing exploits the fact that much of an image is redundant, or sparse, in terms of the information it contains. Specially designed lenses and filters can sift through the large pile of data and automatically pick out the targets of interest, thereby reducing the computational overheads. Magaña-Loaiza et al. combined compressive sensing with ideas in ghost imaging, a technique in which the correlations between quantum-mechanically entangled photons can be used to build up an image of an object with photons that have not interacted with the object directly. The authors demonstrate that such a combination of advanced imaging techniques can be used to track a moving target, requiring many fewer measurements to do so, and describe how such a resource-efficient strategy is applicable to real-world applications of stealth imaging of moving targets.

Appl. Phys. Lett. 102, 231104 (2013).

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