A new architecture, naked-eye ghost imaging via photoelectric feedback, is developed that avoids computer algorithm processing. Instead, the proposed scheme uses a photoelectric feedback loop to first realize the correlation (multiplication) process of the traditional ghost imaging system. Then, the vision persistence effect of the naked eye is exploited to implement the integral process and to generate negative images. Two kinds of feedback circuits, the digital circuit and the analog circuit, are presented that can achieve a feedback operation. Based on this design, high-contrast real-time imaging of moving objects is obtained via a special pattern-scanning architecture on a low-speed light-modulation mask.

The performances of ghost imaging and conventional imaging in photon shot noise cases are investigated. We define an imaging signal-to-noise ratio called SNR^tran where only the object’s transmission region is used to evaluate the imaging quality and it can be applied to ghost imaging (GI) with any random pattern. Both the values SNRGItran of GI and SNRCItran of conventional imaging in photon shot noise cases are deduced from a simple statistical analysis. The analytical results, which are backed up by numerical simulations, demonstrate that the value SNRGItran is related to the ratio between the object’s transmission area A_o and the number density of photons illuminating the object plane I_o, which is similar to the theoretical results based on the first principle of GI with a Gaussian speckle field deduced by B. I. Erkmen and J. H. Shapiro [in Adv. Opt. Photonics 2, 405–450 (2010)]. In addition, we also show that the value SNRCItran will be larger than SNRGItran when A_o is beyond a threshold value.

An aberration-free imaging technique was used to design a double-spherically bent crystal spectrometer with high energy and spatial resolutions to ensure that the individual spectral lines are represented as perfectly straight lines on the detector. After obtaining the matched parameters of the two crystals via geometry-based optimization, an alignment method was employed to allow the spacing between the crystals and the detector to be coupled with the source. The working principle of this spectrum-measuring scheme was evaluated using a Cu X-ray tube. High-quality spectra with energy resolutions (E/ΔE) of approximately 3577 were obtained for a relatively large source size.

Subtractive imaging is used to suppress the axial sidelobes and improve the axial resolution of 4pi microscopy with a higher-order radially polarized (RP) Laguerre–Gaussian (LG) beam. A solid-shaped point spread function (PSF) and a doughnut-shaped PSF with a dark spot along the optical axis are generated by tightly focusing a higher-order RP-LG beam and a modulated circularly polarized beam, respectively. By subtracting the two images obtained with those two different PSFs, the axial sidelobes of the subtracted PSF are reduced from 37% to about 10% of the main lobe, and the axial resolution is increased from 0.21λ to 0.15λ.

We develop a source and mask co-optimization framework incorporating the minimization of edge placement error (EPE) and process variability band (PV Band) into the cost function to compensate simultaneously for the image distortion and the increasingly pronounced lithographic process conditions. Explicit differentiable functions of the EPE and the PV Band are presented, and adaptive gradient methods are applied to break symmetry to escape suboptimal local minima. Dependence on the initial mask conditions is also investigated. Simulation results demonstrate the efficacy of the proposed source and mask optimization approach in pattern fidelity improvement, process robustness enhancement, and almost unaffected performance with random initial masks.

Dispersed fringe sensors are a promising approach for sensing the large-scale physical step between adjacent segments with acceptable accuracy. However, the nature of dispersion in a dispersed fringe sensor leads to the ideal dispersed fringe pattern becoming vulnerable to noise, particularly at low light levels. A reliable merit-function-based algorithm with an active actuation is introduced here. The feasibility of our algorithm is numerically demonstrated, and Monte Carlo experiments for different signal-to-noise ratios are conducted to assess its robustness. The results show that the method is valid even when the signal-to-noise ratio is as low as 1.

In our Letter, two kinds of handwriting traces, colored and colorless, are studied by means of reflectance transformation imaging. The illumination direction and rendering mode can be changed alternatively to obtain two-dimensional and three-dimensional details of the traces that are not recognized easily by naked eyes. Furthermore, an objective evaluation method without reference is applied to evaluate the reconstructed images, which provides a basis for setting the illumination direction and rendering mode. Therefore, the handwriting trace information including the written content, the writing features, and the stroke order features can be obtained objectively and accurately.

The resolution of a conventional imaging system based on first-order field correlation can be directly obtained from the optical transfer function. However, it is challenging to determine the resolution of an imaging system through random media, including imaging through scattering media and imaging through randomly inhomogeneous media, since the point-to-point correspondence between the object and the image plane in these systems cannot be established by the first-order field correlation anymore. In this Letter, from the perspective of ghost imaging, we demonstrate for the first time, to the best of our knowledge, that the point-to-point correspondence in these imaging systems can be quantitatively recovered from the second-order correlation of light fields, and the imaging capability, such as resolution, of such imaging schemes can thus be derived by analyzing second-order autocorrelation of the optical transfer function. Based on this theoretical analysis, we propose a lensless Wiener–Khinchin telescope based on second-order spatial autocorrelation of thermal light, which can acquire the image of an object by a snapshot via using a spatial random phase modulator. As an incoherent imaging approach illuminated by thermal light, the lensless Wiener–Khinchin telescope can be applied in many fields such as X-ray astronomical observations.

In this Letter, we propose an advanced framework of ghost edge imaging, named compressed ghost edge imaging (CGEI). In the scheme, a set of structured speckle patterns with pixel shifting illuminate on an unknown object. The output is collected by a bucket detector without any spatial resolution. By using a compressed sensing algorithm, we obtain horizontal and vertical edge information of the unknown object with the bucket detector detection results and the known structured speckle patterns. The edge is finally constructed via two-dimensional edge information. The experimental and numerical simulations results show that the proposed scheme has a higher quality and reduces the number of measurements, in comparison with the existing edge detection schemes based on ghost imaging.

The precise alignment of a high-performance telescope is a key factor to ensure the imaging quality. However, for telescopes with a wide field of view, the images are sometimes under-sampled. To study the effects of under-sampled images on the precision of telescope alignment, numerical simulations are implemented with the stochastic parallel gradient descent algorithm. The results show that the alignment program can converge stably and quickly. However, with the reduction of the full width at half-maximum of images, the relative residual errors increase from 9.5% to 19.5%, and the wavefront errors raise from 0.0972λ to 0.1074λ, indicating that the accuracy of the alignment decreases.