Modern cameras typically use an array of millions of detector pixels to capture images. By
contrast, single-pixel cameras use a sequence of mask patterns to filter the scene along with …

Since their inception in the 1930–1960s, the research disciplines of computational imaging
and machine learning have followed parallel tracks and, during the last two decades …

In this manuscript, we propose a novel framework of computational ghost imaging, ie, ghost
imaging using deep learning (GIDL). With a set of images reconstructed using traditional GI …

We report an experimental proof of principle for ghost imaging in the hard-x-ray energy
range. We use a synchrotron x-ray beam that is split using a thin crystal in Laue diffraction …

Computational imaging enables retrieval of the spatial information of an object with the use
of single-pixel detectors. By projecting a series of known random patterns and measuring …

Ghost imaging has been a subject of interest to the quantum optics community for the past
20 years. Initially seen as manifestation of quantum spookiness, it is now recognized as …

The interest in a system often resides in the interplay among different parameters governing
its evolution. It is thus often required to access many of them at once for a complete …

Whereas modern digital cameras use a pixelated detector array to capture images, single-
pixel imaging reconstructs images by sampling a scene with a series of masks and …

We present a new technique, differential ghost imaging (DGI), which dramatically enhances
the signal-to-noise ratio (SNR) of imaging methods based on spatially correlated beams …

Ghost-imaging experiments correlate the outputs from two photodetectors: a high spatial-
resolution (scanning pinhole or charge-coupled-device camera) detector that measures a …