Related papers: Unsighted deconvolution ghost imaging
We propose a novel grayness index for finding gray pixels and demonstrate its effectiveness and efficiency in illumination estimation. The grayness index, GI in short, is derived using the Dichromatic Reflection Model and is learning-free.…
Incoherent Diffraction Imaging - IDI - is a diffraction-based imaging technique that has been recently proposed to exploit the partial coherence of incoherently scattered light to retrieve structural information from the scattering centers.…
The capture of transient optical waveforms is critical to reveal dynamical phenomena in various fields. However, fast and sensitive mid-infrared (MIR) measurements are typically limited by processing bandwidth and detection sensitivity of…
Much more image details can be resolved by improving the system's imaging resolution and enhancing the resolution beyond the system's Rayleigh diffraction limit is generally called super-resolution. By combining the sparse prior property of…
We present a theoretical study of ghost imaging based on correlated beams arising from parametric down-conversion, and which uses balanced homodyne detection to measure both the signal and idler fields. We analytically show that the…
We present GI-GS, a novel inverse rendering framework that leverages 3D Gaussian Splatting (3DGS) and deferred shading to achieve photo-realistic novel view synthesis and relighting. In inverse rendering, accurately modeling the shading…
The use of x-ray imaging in medicine and other research is well known. Generally, the image quality is proportional to the total flux, but high photon energy could severely damage the specimen, so how to decrease the radiation dose while…
Conventional imaging at low light level requires hundreds of detected photons per pixel to suppress the Poisson noise for accurate reflectivity inference. In this letter, we propose a high-efficiency photon-limited imaging technique, called…
We propose a computational ghost imaging scheme using customized pink noise speckle pattern illumination. By modulating the spatial frequency amplitude of the speckles, we generate speckle patterns with a significant positive spatial…
X-ray imaging is a prevalent technique for non-invasively visualizing the interior of the human body and opaque instruments. In most commercial x-ray modalities, an image is formed by measuring the x-rays that pass through the object of…
Ill-posed image reconstruction problems appear in many scenarios such as remote sensing, where obtaining high quality images is crucial for environmental monitoring, disaster management and urban planning. Deep learning has seen great…
We outline and experimentally demonstrate a method to image pure phase objects using traditional quantum ghost imaging with single pixel detectors. We provide a theoretical description of the process, showing how phase information is…
A wide range of diagnostic information in medicine is currently obtained using radioactive tracers. While central to nuclear medicine, these methods are inherently constrained: radiation dose limits repeat examinations, short tracer…
The current ghost imaging phase reconstruction schemes require either complex optical systems, Fourier transform steps, or iterative algorithms, which may increase the difficulty of system design, cause phase retrieval error or take too…
The InfraRed Imaging Spectrograph (IRIS) is a first-light instrument for the Thirty Meter Telescope (TMT) that will be used to sample the corrected adaptive optics field by NFIRAOS with a near-infrared (0.8 - 2.4 $\mu$m) imaging camera and…
The Fourier-Transform ghost imaging of both amplitude-only and pure-phase objects was experimentally observed with classical incoherent light at Fresnel distance by a new lensless scheme. The experimental results are in good agreement with…
We present a framework for computational ghost imaging based on deep learning and customized pink noise speckle patterns. The deep neural network in this work, which can learn the sensing model and enhance image reconstruction quality, is…
Artificial intelligence has recently been widely used in computational imaging. The deep neural network (DNN) improves the signal-to-noise ratio of the retrieved images, whose quality is otherwise corrupted due to the low sampling ratio or…
Ghost imaging and differential ghost imaging are well-known imaging techniques based on the use of both classical and quantum correlated states of light. Since the existence of correlations has been shown to be the main resource to…
X-ray "ghost" imaging has drawn great attention for its potential to lower radiation dose in medical diagnosis. For practical implementation, however, the efficiency and image quality have to be greatly improved. Here we demonstrate a…