Ghost imaging (also called "coincidence imaging") is a technique that produces an image of an object by combining information from two light detectors: a conventional, multi-pixel detector that doesn't view the object, and single-pixel (bucket) detector that does view the object. Whether or not this technique requires quantum entanglement of photons for explanation is debated.
The first demonstrations of ghost imaging were based on the quantum nature of light. Specifically, quantum correlations between photon pairs were utilized to build up an image. One of the photons of the pair strikes the object and then the bucket detector while the other follows a different path to a (multi-pixel) camera. The camera is constructed to only record pixels from photons that hit both the bucket detector and the camera's image plane.
Later experiments indicated that the correlations between the light beam that hits the camera and the beam that hits the object may be explained by purely classical physics. If quantum correlations are present, the signal-to-noise ratio of the reconstructed image can be improved. In 2009 'pseudothermal ghost imaging' and 'ghost diffraction' were demonstrated by implementing the 'computational ghost-imaging' scheme, which relaxed the need to evoke quantum correlations arguments for the pseudothermal source case. The exact role of quantum and classical correlations in ghost imaging is still controversial.
Recently, it was shown that the principles of 'Compressed-Sensing' can be directly utilized to reduce the number of measurements required for image reconstruction in ghost imaging. This technique allows an N pixel image to be produced with far less than N measurements and may have applications in LIDAR and microscopy.
A simple example clarifies the basic principle of ghost imaging. Imagine two transparent boxes: one that is empty and one that has an object within it. The back wall of the empty box contains a grid of many pixels (i.e. a camera), while the back wall of the box with the object is a large single-pixel (a bucket detector). Next, shine laser light into a beamsplitter and reflect the two resulting beams such that each passes through the same part of its respective box at the same time. For example, while the first beam passes through the empty box to hit the pixel in the top-left corner at the back of the box, the second beam passes through filled box to hit the top-left corner of the bucket detector.
Now imagine moving the laser beam around in order to hit each of the pixels at the back of the empty box, meanwhile moving the corresponding beam around the box with the object. While the first light beam will always hit a pixel at the back of the empty box, the second light beam will sometimes by blocked by the object and will not reach the bucket detector. A processor receiving a signal from both light detectors only records a pixel of an image when light hits both detectors at the same time. In this way, a silhouette image can be constructed, even though the light going towards the multi-pixel camera did not touch the object.
In this simple example, the two boxes are illuminated one pixel at a time. However, using quantum correlation between photons from the two beams, the correct image can also be recorded using complex light distributions. Also, the correct image can be recorded using only the single beam passing through a computer controlled light modulator to a single-pixel detector.
- 'Ghost Imaging with a Single Detector' by Y.Bromberg, O.Katz and Y.Silberberg
- 'Computational Ghost Imaging' by J.Shapiro
- 'Compressive Ghost Imaging' by O.Katz, Y.Bromberg and Y.Silberberg
- Ryan S. Bennink, Sean J. Bentley, and Robert W. Boyd (2002). Physical Review Letters 89: 113601. Bibcode:2002PhRvL..89k3601B. doi:10.1103/PhysRevLett.89.113601.
- Quantum camera snaps objects it cannot 'see'[dead link] by Belle Dume, New Scientist, 2 May 2008. Accessed July 2008
- Air Force Demonstrates 'Ghost Imaging' By Sharon Weinberger, Wired, 3 June 2008. Accessed July 2008
- Army scientists' 19 patents lead to quantum imaging advances Army Research Laboratory News DECEMBER 19, 2013. Accessed Feb 2014