Ghost imaging is a computational imaging technique that, when combined with human vision, can image an object that cannot be seen by the person. It is a new development in using artificial intelligence towards enhancing human vision.
Daniele Faccio from the University of Glasgow in the UK has presented the new findings at the Optica, Imaging and Applied Optics Congress, titled "Non-Line-of-Sight (NLoS) Imaging and Imaging through Scattering Media."
Imaging is possible by correlating a projected light pattern that interacts with the object and a reference pattern that does not. This is the first time researchers used a human visual system having a real person view the light patterns instead of a camera. The brain's visual response is recorded and used as feedback for an algorithm that determines how to reshape the projected light patterns and reconstructs the final image.
EEG technique was used to estimate the intensity of light transmitted by the object and diffused from the white wall, information that was fed into a neurofeedback loop used to reconstruct the image. When the EEG signal fell below a certain threshold, it was concluded that the light pattern didn't overlap with the object and could be automatically removed or carved out in real time by the system.
Through this technique, researchers could successfully reconstruct 16×16 pixel images of simple objects that could not be seen. They also demonstrated that the carving out process helped reduce the observation time needed for image reconstruction to about 1 minute.
"We believe that this work provides ideas that one day might be used to bring together human and artificial intelligence. The next steps in this work range from extending the capability to provide 3D depth information to looking for ways to combine multiple information from multiple viewers at the same time", says Daniele Faccio, Professor of Quantum Technologies, School of Physics and Astronomy, University of Glasgow
