High frame-rate computational ghost imaging system using an optical fiber phased array and a low-pixel APD array.

Recent researches showed that the traditional ghost imaging (TGI) using pseudo-thermal light can be affected by the solid scattering material placed between the object and the light source. This scattering case might also affect the computational ghost imaging (CGI) and is considered in this paper. Different from the TGI system modeled by Huygens–Fresnel theory in continuous coordinates, in CGI the use of computer-generated patterns with the controllable size ( $d$ ) of each pixel discretizes the object space into the $d$ -based pixel-grids. Therefore, how the CGI system is affected by the scatters depends on the distribution of the scattered light on these discretized grids instead of in continuous coordinates, which has not been explored. In this paper, we demonstrate that the “anti-scattering” capacity of CGI is governed by the discrete point-scattering-function (DPSF) that is determined by $\frac{{w_{0}}}{d}$ ( $w_{0}$ : the width of point-scattering-function of the scatters). We show that the blurry effect on the reconstructed image is visible as $d\ll\frac{{w_{0}}}{2}$ , but can be highly restrained as $d$ increasing to be comparable to $\frac{w_{0}}{2}$ or larger. Furthermore, $d$ determines the spatial resolution power of CGI. In the given CGI system, the minimum $d$ of $\sim\frac{{w}_{0}}{5}$ could be achieved with maintaining the behavior of “scattering-free”.

Computational ghost imaging system with 4-connected-region-optimized Hadamard pattern sequence

Influence of detector response speed on the contrast-to-noise ratio of reflective ghost imaging

The analysis tools of traditional optical systems, such as modulation transfer functions, point spread functions, resolution test charts etc. are often not sufficient when analyzing computational imaging systems. Computational imaging systems benefit from the combined use of optics and electronics for accomplishing a given imaging or system task. In traditional optical systems the goal is essentially to form images that precisely depict a given object. Electronics are not required to form clear images, but could be required to analyze the images. In computational imaging systems specialized images are formed by generalized aspheric optical elements that are jointly optimized with the electronic processing. The specialized images formed at a detector are not necessarily clear images. Electronic processing is used to remove the image blur or otherwise form a final image. Computational imaging systems offer the advantage of increased performance and decreased size, weight, and cost over traditional optical systems. The Ambiguity Function (AF), traditionally used for the design of radar waveforms, plays an important role in computational imaging systems. The AF provides a concise analysis of the optical transfer functions of imaging systems over defocus. The Wigner Distribution (WD), traditionally used for the design of time-varying systems, is related to the AF and provides a concise analysis of the point spread functions (PSF) of imaging systems over defocus. We will describe the relationships and utility of these functions to computational imaging systems.

In this paper, a preliminary study related to the detection of breast cancer based on a computational microwave imaging system is presented at K-band frequencies. In comparison to normal tissues, the different dielectric properties (permittivity and conductivity) of the malignant tissues can be exploited in order to detect the presence of tumour through a microwave imaging system. This work demonstrates the detection of breast tumour as an application of a computational imaging technique by leveraging the concept of the dynamic metasurface antenna (DMA) aperture as a transmitter. In this framework, the computational imaging aperture can provide a compact system design with a low-cost deployment for detecting tumours in early-stage, and this can speed up the screening process of the population at risk. Particularly, early detection of Stage 1 can help with the determination of the best treatment method and enhance a patient's prognosis.

Computational imaging is a proven strategy for obtaining high-quality images with fast acquisition rates and simpler hardware. Metasurfaces provide exquisite control over electromagnetic fields, enabling the radiated field to be molded into unique patterns. The fusion of these two concepts can bring about revolutionary advances in the design of imaging systems for security screening. In the context of computational imaging, each field pattern serves as a single measurement of a scene; imaging a scene can then be interpreted as estimating the reflectivity distribution of a target from a set of measurements. As with any computational imaging system, the key challenge is to arrive at a minimal set of measurements from which a diffraction-limited image can be resolved. Here, we show that the information content of a frequency-diverse metasurface aperture can be maximized by design, and used to construct a complete millimeter-wave imaging system spanning a 2 m by 2 m area, consisting of 96 metasurfaces, capable of producing diffraction-limited images of human-scale targets. The metasurfacebased frequency-diverse system presented in this work represents an inexpensive, but tremendously flexible alternative to traditional hardware paradigms, offering the possibility of low-cost, real-time, and ubiquitous screening platforms.

Demonstration of computational ghost imaging through fog

The use of flat panel detectors in computed tomography (CT) systems can improve resolution, reduce system cost, and add operational flexibility by combining fluoroscopy and radiography applications within CT systems. However, some prior studies have suggested that flat panel detectors would not perform well in CT applications due to their lack of high dynamic range, lag artifacts, and inadequate frame rate. The purpose of this study was to perform a physical evaluation of a prototype flat panel detector capable of high frame rates and extended dynamic range. The flat panel detector used had a pixel size of 194 microns and a matrix size of 2048x1536. The detector could be configured for several combinations of frame rate and matrix size up to 750 frames per second for a 512x16 matrix size with 4x4 binning. The evaluation was performed in terms of the MTF and DQE as a function of frame rate and exposure at the IEC RQA5 (~75 kVp, 21 mm Al) beam quality. The image lag was evaluated in terms of temporal-frequency dependent transfer function. Offset shift were also evaluated. Preliminary results indicate 0.1 MTF at 0.92 cycles/mm and DQE(0) of approximately 0.8, 0.6, 0.4, and 0.22 at 0.144, 0.065, 0.035, and 0.008 mR per frame exposures. The temporal MTF exhibited a low-frequency drop and a value of 0.5 at the Nyquist frequency. Offset shift was negligible. Considering high frame rate capabilities of the new detector, the results suggest that the detector has potential for use in real-time CT applications including CT angiography.

In the modern tactical imaging environment, new computational imaging (CI) systems and algorithms are being used to improve speed and accuracy for detection tasks. Therefore, a measurement technique is needed to predict the performance of complex non-shift invariant EO/IR imaging systems, including CI systems. Detection performance of traditional imaging systems can be modeled using current system metrics and measurements such as Modulation Transfer Function (MTF), Signal to Noise (SNR), and instantaneous Field of View (iFOV). In this correspondence, we propose a technique to experimentally measure a detection sensitivity metric for non-traditional CI systems. The detection sensitivity metric predicts the upper bound of linear algorithm performance though evaluation of a matched filter. The experimental results are compared with theoretical expected values though the Night Vision Integrated Performance Model (NV-IPM). Additionally, we demonstrate the experimental results for a variety of imaging systems (IR, visible, and color), target sizes and orientations, as well as SNR values. Our results demonstrate how this detection sensitivity metric can be measured to provide additional insight into the final system performance.

Origami is the art of paper folding that allows a single flat piece of paper to assume different 3D shapes depending on the fold patterns and the sequence of folding. Using the principles of origami along with computation imaging technique the authors demonstrate a versatile shape‐morphing microwave imaging array with reconfigurable field‐of‐view and scene‐adaptive imaging capability. Microwave/millimeter‐wave based array imaging systems are expected to be the workhorse for sensory perception of future autonomous intelligent systems. The imaging capability of a planar array‐based systems operating in complex scattering conditions have limited field‐of‐view and lack the ability to adaptively reconfigure resolution. To overcome this, here, deviations from planarity and isometry are allowed, and a shape‐morphing computational imaging system is demonstrated. Implemented on a reconfigurable Waterbomb origami surface with 22 active metasurface panels that radiate near‐orthogonal modes across 17–27 GHz, capability to image complex 3D objects in full details minimizing the effects of specular reflections in diffraction‐limited sparse imaging with scene adaptability, reconfigurable cross‐range resolution, and field‐of‐view is demonstrated. Such electromagnetic origami surfaces, through simultaneous surface shape‐morphing ability (potentially with shape‐shifting electronic materials) and electromagnetic field programmability, opens up new avenues for intelligent and robust sensing and imaging systems for a wide range of applications.

Microscopic video imaging techniques that combine high frame rates with large fields of view (FOV) are essential in applications ranging from biomedical microscopy to industrial inspection. However, simultaneously achieving both high frame rates and large FOVs presents significant challenges. One strategy involves on-chip pixel binning—a process essentially equivalent to downsampling—that boosts the frame rate of area detectors while improving the signal-to-noise ratio in optical imaging. In the context of relay-projection microscopic telescopy (rPMT), a novel computational microscopic imaging technique, pixel binning increases the frame rate but at the cost of enlarging the sampling interval in the Fourier spectrum plane. Since the object plane and the Fourier spectrum plane are linked by Fourier transform, the FOV in the object plane is consequently reduced, potentially failing to cover the entire object, leading to information loss and possible object reconstruction failure. A similar issue may arise when using detectors with inherently large pixel sizes. To address the issue of reduced FOV in the object plane, we propose applying interpolation-based upsampling to the spatial power spectrum images during preprocessing. This adjustment of the sampling interval in the Fourier spectrum plane effectively expands the object plane's FOV, optimally utilizes the spatial power spectrum information, and facilitates successful object reconstruction. We first validated the feasibility and effectiveness of this method experimentally. Subsequently, we analyzed the impact of the upsampling rate on reconstruction quality and developed a procedure for estimating the optimal upsampling rate to achieve high-efficiency, high-quality reconstructions. Finally, we conducted a comparative analysis of various interpolation algorithms, such as nearest, bilinear, and bicubic interpolation, and their effects on object reconstruction outcomes. By integrating on-chip pixel binning with interpolation-based upsampling, imaging frame rates of rPMT can be enhanced while maintaining a consistent FOV in the object plane. This technique holds significant potential for advancing dynamic microscopic video imaging methods with high frame rate and large FOV, thereby contributing to the evolution of computational microscopic imaging technologies.

In this paper, we report recent progress that has been made in the development of a high frame rate duplex HF ultrasound system with both B-scan imaging and Doppler flow measurements. A 32-channel HF analog beamformer module with transmitting focusing and dynamic focusing on reception was implemented. High-speed timing circuits were used to achieve high imaging frame rate by reducing the acquisition overhead. Therefore, the frame rate of the system relies only on the field of view. The system also included a 64-channel analog front-end pulser/receiver, a HF pulsed-wave (PW) Doppler module, a PC with a 200MS/s 14-bit PCI A/D card and real-time Labview software for data acquisition and image display. A wire phantom used to evaluate the resolution of the system. High frame rate B-scan images of mouse hearts have been obtained, as well as the PW Doppler blood flow velocity profiles at the specified location. The system is able to acquire real-time B-mode images at a rate greater than 400 frames per second in a 4.8 × 13 mm field of view. In vivo mouse experiment results show a promising future of this system in small animal research. The system will be expanded to support future arrays with more elements.

Diffractive lens (DLs) computational imaging promises lightweight infrared imaging. However, it is still challenging to accurately obtain the degradation of DLs computational imaging systems to achieve high-quality imaging. Degradation estimation methods based on image-to-image are the most feasible way, but existing methods face the problem of low accuracy for severe degradation estimation. In this paper, we proposed a severe degradation estimation framework based on KernelNet, and realized the improvement of the accuracy of severe degenerate estimation by more than 1.13 dB. Furthermore, DyUnet, an image restoration network, was proposed, which is based on dynamic convolution. The results of the mid-wave diffractive lens infrared computational imaging system indicated that our method achieved high-quality imaging results comparable to the conventional one, while the number of optical elements was reduced from 7 to 2, and the weight was reduced by 50%.

The digital revolution changed film production and its aesthetics in many ways. Although motion is a defining feature of moving images, it is also one of their most problematic aspects because of blurred images or other signal processing artifacts. An artistic research project was conducted to test the effects of high frame rates (HFR) on visual perception. Typical camera movements were recorded in different frame rates (24 / 48 / 96 fps) to generate test sequences for a cinema experiment. 69 participants were measured with an SMI eye tracking device and a questionnaire in a within subjects design. The results show that the participants valued the higher image quality of HFR, but rated the standard frame rate as more realistic and indicated more presence. Moreover, HFR produced a higher number of fixations than the standard frame rate. Open questions for future research projects on HFR will be discussed.

The purpose of this study was to assess whether or not high frame rate (HFR) videos recorded using high-speed digital imaging (HSDI) improve the visual recognition of the motions of the laryngopharyngeal structures during pharyngeal swallow in fiberoptic endoscopic evaluation of swallowing (FEES). Five healthy subjects were asked to swallow 0.5ml water under fiberoptic nasolaryngoscopy. The endoscope was connected to a high-speed camera, which recorded the laryngopharyngeal view throughout the swallowing process at 4000 frames/s (fps). Each HFR video was then copied and downsampled into a standard frame rate (SFR) video version (30 fps). Fifteen otorhinolaryngologists observed all of the HFR/SFR videos in random order and rated the four-point ordinal scale reflecting the degree of visual recognition of the rapid laryngopharyngeal structure motions just before the 'white-out' phenomenon. Significantly higher scores, reflecting better visibility, were seen for the HFR videos compared with the SFR videos for the following laryngopharyngeal structures: the posterior pharyngeal wall (p=0.001), left pharyngeal wall (p=0.015), right lateral pharyngeal wall (p=0.035), tongue base (p=0.005), and epiglottis tilting (p=0.005). However, when visualized with HFR and SFR, 'certainly clear observation' of the laryngeal structures was achieved in <50% of cases, because all the motions were not necessarily captured in each video. These results demonstrate the use of HSDI in FEES makes the motion perception of the laryngopharyngeal structures during pharyngeal swallow easier in comparison to SFR videos with equivalent image quality due to the ability of HSDI to depict the laryngopharyngeal motions in a continuous manner.