Point Spread Function Of System Research Articles

Lensless light-field imaging using LMI

Light-field imaging is widely used in many fields, such as computer vision, graphics, and microscopy imaging, to record high-dimensional light information for abundant visual perception. However, light-field imaging systems generally have high system complexity and limited resolution. Over the last decades, lensless imaging systems have attracted tremendous attention to alleviate the restrictions of lens-based architectures. Despite their advantages, lensless light-field imaging introduces significant errors in light-field reconstruction. This paper introduces a novel, to our knowledge, light field moment imaging-based lensless imaging system (LMI-LIS) aiming to improve the quality of light-field reconstruction. The proposed approach first uses light field moment imaging (LMI) with a sinc angular distribution model of the light field to extract the encoded information of the scene for each sub-aperture area. Meanwhile, the corresponding sub-aperture point spread function is segmented from the system point spread function. Finally, sub-aperture images of the scene are reconstructed separately for each sub-aperture area. To evaluate the light-field reconstruction performance, the imaging quality and angular consistency of different lensless light-filed imaging methods are compared through digital refocusing, epipolar plane image, peak signal-to-noise ratio, and structural similarity index. Furthermore, the effectiveness of the proposed methodology is verified using experimental results and theoretical analysis. It is demonstrated that lensless light-field imaging using LMI and the sinc model of the angular distribution achieves high-quality sub-aperture images.

Differential Lucy-Richardson-Rosen algorithm for near diffraction-limited image restoration assisting by a wavefront sensor

Lucy-Richardson-Rosen algorithm (LR2A) is one of the most important tools for image restoration, especially in computer vision, target imaging and so on. However, the performance of the LR2A can be affected by large optical aberration and imaging noise and even failure under severe environment. To address the mentioned problem, we proposed a new Differential Lucy-Richardson-Rosen Algorithm(D-LR2A) to reduce the influence of optical aberrations and detection noise with advantages of faster speed of convergence and better restoration quality. In the modified optical configuration, a Hartmann-Shack wavefront sensor is employed to measure optical aberration and estimate accurately the Point Spread Function (PSF) of the optical imaging system. The numeric and experimental results show that the proposed method can be used to restore images with large optical aberration and worse noise level. Besides that, it also has faster speed, better restoration quality, and thus easier application as compared to those of LR2A

Image scanning microscopy reconstruction by autocorrelation inversion

Abstract Confocal laser scanning microscopy (CLSM) stands out as one of the most widely used microscopy techniques thanks to its three-dimensional imaging capability and its sub-diffraction spatial resolution, achieved through the closure of a pinhole in front of a single-element detector. However, the pinhole also rejects useful photons, and beating the diffraction limit comes at the price of irremediably compromising the signal-to-noise ratio (SNR) of the data. Image scanning microscopy (ISM) emerged as the rational evolution of CLSM, exploiting a small array detector in place of the pinhole and the single-element detector. Each sensitive element is small enough to achieve sub-diffraction resolution through the confocal effect, but the size of the whole detector is large enough to guarantee excellent collection efficiency and SNR. However, the raw data produced by an ISM setup consists of a 4D dataset, which can be seen as a set of confocal-like images. Thus, fusing the dataset into a single super-resolved image requires a dedicated reconstruction algorithm. Conventional methods are multi-image deconvolution, which requires prior knowledge of the system point spread functions (PSFs), or adaptive pixel reassignment (APR), which is effective only on a limited range of experimental conditions. In this work, we describe and validate a novel concept for ISM image reconstruction based on autocorrelation inversion. We leverage unique properties of the autocorrelation to discard low-frequency components and maximize the resolution of the reconstructed image without any assumption on the image or any knowledge of the PSF. Our results push the quality of the ISM reconstruction beyond the level provided by APR and open new perspectives for multi-dimensional image processing.

Unsupervised deep learning method for single image super-resolution of the thick pinhole imaging system using deep image prior

Thick pinhole imaging system is widely used for diagnosing intense pulsed radiation sources. However, owing to the trade-off among spatial resolution, field of view (FOV) and signal-to-noise ratio (SNR), the imaging system normally falls short in achieving high-precision spatial diagnosis. In this paper, we propose an unsupervised deep learning method for single image super-resolution (SISR) of the thick pinhole imaging system. The point spread function (PSF) of the imaging system is obtained by analytical calculation and Monte Carlo simulation methods, and the mathematical model of the imaging system is established using a linear equation. To solve the ill-posed inverse problem, we adopt randomly initialized deep convolutional neural networks (DCNNs) as an image prior without pre-training, which is named deep image prior (DIP). The results demonstrate that, by utilizing the SISR technique to increase the number of pixels in reconstructed images, the proposed DIP algorithm can mitigate the spatial resolution degradation caused by an insufficient spatial sampling frequency of the camera. Compared with various classical algorithms, the proposed DIP algorithm exhibits superior capabilities in recovering high-frequency signals and suppressing ringing artifacts. Furthermore, the convergence and robustness of the proposed DIP algorithm under different random seeds and SNR conditions are also verified.

Calculating point spread functions: methods, pitfalls, and solutions

The knowledge of the exact structure of the optical system point spread function (PSF) enables a high-quality image reconstruction in fluorescence microscopy. Accurate PSF models account for the vector nature of light and the phase and amplitude modifications. Most existing real-space-based PSF models fall into a sampling pitfall near the center position, yielding to the violation of energy conservation. In this work, we present a novel, to the best of our knowledge, Fourier-based techniques for computing vector PSF and compare them to the state-of-the-art. Our methods are shown to satisfy the physical condition of the imaging process. They are reproducible, computationally efficient, easy to implement, and easy to modify to represent various imaging modalities.

Point Spread Function And Spatial Resolution Analysis Of Multi-Focus Plenoptic Cameras

With the recent development of plenoptic cameras, light field imaging has become a reliable solution for 3D metrology. Plenoptic cameras allow recovering the 3D information of a scene with a single acquisition and only one camera. These advantages make light field imaging particularly interesting for the metrology of two-phase flows. The measurement depth of a back-light imaging setup can be determined by the calibration of the Point Spread function (PSF) of the optical system. This study provides a method adapted to multi-focus plenoptic cameras to measure the PSF width from reconstructed images. We used a calibration target composed of multiple calibrated opaque disks and a diffuse backlight illumination set-up. The PSF width is estimated by measuring the grayscale gradient at the interface of the images of the disks. Coupled with the depth information provided by the plenoptic camera, we obtained the evolution of the PSF at different depth planes. The information on the PSF enables us to obtain the focus criterion, which sets the limits of the measurement volume. The spatial resolution of the reconstructed images is obtained from the PSF. The results obtained for the resolution as a function of virtual depth are consistent with results from previous studies.

Aberration pre-correction for a simple optical system of HMDs.

Head-mounted displays (HMDs) are becoming increasingly popular as a crucial component of virtual reality (VR). However, contemporary HMDs enforce a simple optical structure due to their constrained form factor, which impedes the use of multiple lens elements that can reduce aberrations in general. As a result, they introduce severe aberrations and imperfections in optical imagery, causing visual fatigue and degrading the immersive experience of being present in VR. To address this issue without modifying the hardware system, we present a novel, to the best of our knowledge, software-driven approach that compensates for the aberrations in HMDs in real time. Our approach involves pre-correction that deconvolves an input image to minimize the difference between its after-lens image and the ideal image. We characterize the specific wavefront aberration and point spread function (PSF) of the optical system using Zernike polynomials. To achieve higher computational efficiency, we improve the conventional deconvolution based on hyper-Laplacian prior by adopting a regularization constraint term based on L2 optimization and the input-image gradient. Furthermore, we implement our solution entirely on a graphics processing unit (GPU) to ensure constant and scalable real-time performance for interactive VR. Our experiments evaluating our algorithm demonstrate that our solution can reliably reduce the aberration of the after-lens images in real time.

Robustness of single random phase encoding lensless imaging with camera noise.

In this paper, we assess the noise-susceptibility of coherent macroscopic single random phase encoding (SRPE) lensless imaging by analyzing how much information is lost due to the presence of camera noise. We have used numerical simulation to first obtain the noise-free point spread function (PSF) of a diffuser-based SRPE system. Afterwards, we generated a noisy PSF by introducing shot noise, read noise and quantization noise as seen in a real-world camera. Then, we used various statistical measures to look at how the shared information content between the noise-free and noisy PSF is affected as the camera-noise becomes stronger. We have run identical simulations by replacing the diffuser in the lensless SRPE imaging system with lenses for comparison with lens-based imaging. Our results show that SRPE lensless imaging systems are better at retaining information between corresponding noisy and noiseless PSFs under high camera noise than lens-based imaging systems. We have also looked at how physical parameters of diffusers such as feature size and feature height variation affect the noise robustness of an SRPE system. To the best of our knowledge, this is the first report to investigate noise robustness of SRPE systems as a function of diffuser parameters and paves the way for the use of lensless SRPE systems to improve imaging in the presence of image sensor noise.

Super-resolution image reconstruction of a neutron thick pinhole imaging system using image denoiser prior based on half quadratic splitting method

Thick pinhole imaging system is a powerful tool to diagnose intense pulsed radiation sources. However, high spatial resolution of a thick pinhole imaging system cannot be achieved due to the limitation of field of view (FOV) and detection efficiency. In this paper, we propose a novel super-resolution image reconstruction algorithm to improve the spatial resolution of a practical thick pinhole imaging system designed for 14.1 MeV neutrons with 100 mm FOV. Point spread function (PSF) of the imaging system is obtained through complete simulation methods, indicating that the spatial resolution of the imaging system is about 500 μ m. A 4 × super-resolution image reconstruction algorithm using image denoiser as implicit image prior, named image denoiser prior, based on half quadratic splitting (HQS) method is firstly applied to restore more details of neutron sources. The results show that the proposed algorithm performs better than the Richardson-Lucy (RL) algorithm with fewer artifacts and sharper boundaries in reconstructed images. Notably, at a low noise level, the proposed algorithm can surpass the Nyquist sampling limit of 200 μ m, which is determined by the equivalent camera pixel size, to achieve a spatial resolution of 150 μ m.

Transcutaneous Imaging of Rabbit Kidney Using 3-D Acoustic Wave Sparsely Activated Localization Microscopy with a Row-Column-Addressed Array.

Super-resolution ultrasound (SRUS) imaging through localizing and tracking microbubbles, also known as ultrasound localization microscopy (ULM), can produce sub-diffraction resolution images of micro-vessels. We have recently demonstrated 3-D selective SRUS with a matrix array and phase change contrast agents (PCCAs). However, this method is limited to a small field of view (FOV) and by the complex hardware required. This study proposed 3-D acoustic wave sparsely activated localization microscopy (AWSALM) using PCCAs and a 128+128 row-column-addressed (RCA) array, which offers ultrafast acquisition with over 6 times larger FOV and 4 times reduction in hardware complexity than a 1024-element matrix array. We first validated this method on an in-vitro microflow phantom and subsequently demonstrated non-invasively on a rabbit kidney in-vivo. Our results show that 3-D AWSALM images of the phantom covering a 25×25×40 mm 3 volume can be generated under 5 seconds with an 8 times resolution improvement over the system point spread function. The full volume of the rabbit kidney can be covered to generate 3-D microvascular structure, flow speed and direction super-resolution maps under 15 seconds, combining the large FOV of RCA with the high resolution of SRUS. Additionally, 3-D AWSALM is selective and can visualize the microvasculature within the activation volume and downstream vessels in isolation. Sub-sets of the kidney microvasculature can be imaged through selective activation of PCCAs. Our study demonstrates large FOV 3-D AWSALM using an RCA probe. 3-D AWSALM offers an unique in-vivo imaging tool for fast, selective and large FOV vascular flow mapping.

A theragnostic HIFU transducer and system for inherently registered imaging and therapy.

One big challenge with high intensity focused ultrasound (HIFU) is the difficulty in accurate prediction of focal location due to the complex wave propagation in heterogeneous medium even with imaging guidance. This study aims to overcome this by combining therapy and imaging guidance with one single HIFU transducer using the vibro-acoustography (VA) strategy. Based on the VA imaging method, a HIFU transducer consisting of 8 transmitting elements was proposed for therapy planning, treatment and evaluation. Inherent registration between the therapy and imaging created unique spatial consistence in HIFU transducer's focal region in the above three procedures. Performance of this imaging modality was first evaluated through in-vitro phantoms. In-vitro and ex-vivo experiments were then designed to demonstrate the proposed dual-mode system's ability in conducting accurate thermal ablation. Point spread function of the HIFU-converted imaging system had a full wave half maximum of about 1.2 mm in both directions at a transmitting frequency of 1.2 MHz, which outperformed the conventional ultrasound imaging (3.15 MHz) in in-vitro situation. Image contrast was also tested on the in-vitro phantom. Various geometric patterns could be accurately 'burned out' on the testing objects by the proposed system both in vitro and ex vivo. Implementation of imaging and therapy with one HIFU transducer in this manner is feasible and it has potential as a novel strategy for addressing the long-standing problem in the HIFU therapy, possibly pushing this non-invasive technique forward towards wider clinical applications.

On the optical performance of incoherent digital holography for extended 3D objects

Digital Holography (DH) technology has grown fast over the years, offering the possibility to encode complex information from three-dimensional real-world objects onto two-dimensional digital supports. Accessing the object as an entire numerical complex wavefront raised large expectations in the fields of imaging and display. Holographic vision through fog, smoke, and flames in the far infrared (IR) range would be, in principle, applicable to the fields of automotive, video surveillance, and homeland security. However, the need for bulky, high-coherence laser sources has dampened the enthusiasm around the development of holographic cameras for use in such a context. Here, we investigate self-interference digital holography (SIDH) as a method for obtaining refocusable wavefronts by using low-coherence light sources, a category including light bulbs, arc lamps, light-emitting diodes, low-coherence IR lasers, heat sources, and sunlight. We develop and analyze a model to study the optical performance of SIDH in terms of reconstruction distance range, lateral magnification, resolution, and limiting factors. Then, we propose a configuration for reshaping the system Point Spread Function (PSF) and enhancing resolution by tuning the visibility of high-frequency fringes. The model is experimentally verified by imaging various scenes under incoherent illumination in the visible range. As a last testbed, we provide a first proof of concept SIDH imaging in the far IR range by retrieving and refocusing the complex wavefront back-scattered by point sources illuminated by low-coherence IR light.

Non-iterative reconstruction of interferenceless coded aperture correlation holography enabled high quality three-dimensional imaging

Interferenceless coded aperture correlation holography (I-COACH) is a rapidly developing indirect three-dimensional (3D) imaging technique. However the ideal point spread function of imaging system is not obtained in most cases, the object hologram is usually correlated with the system response of a limited-size pinhole during the reconstruction process. As a result, the quality of reconstructed images is contaminated by noise. In this paper, the system response of a limited-size pinhole is regarded as the convolution of the pinhole (as an object) intensity and the ideal point spread function of I-COACH, a mathematical analysis of the background noise is conducted and a general high-quality reconstruction mathematic model of I-COACH system is derived when a limited-size pinhole is used to record point spread hologram, in which the reconstructions and noise is separated. Then a non-iterative cross-correlation reconstruction algorithm has been developed here to achieve high-quality 3D reconstruction. The proposed method has been implemented on a regular I-COACH system in both transmission as well as reflection illumination modes to demonstrate the imaging ability of our method. The experimental results show that high quality reconstructions can be achieved by our proposal with a single-exposure object hologram.

Multi-shaping sparse-continuous reconstruction for an optical coherence tomography sidelobe suppression.

Optical coherence tomography (OCT) images are commonly affected by sidelobe artifacts due to spectral non-uniformity and spectral leakage. Conventional frequency domain spectral shaping methods widen the mainlobe and compromise axial resolution. While image-domain deconvolution techniques can address the trade-off between axial resolution and artifact suppression, their reconstruction quality relies on accurate measurement or estimation of system point spread function (PSF). Inaccurate PSF estimation leads to loss of details in the reconstructed images. In this Letter, we introduce multi-shaping sparse-continuous reconstruction (MSSCR) for an OCT image, a novel, to the best of our knowledge, framework that combines spectral multi-shaping and iterative image reconstruction with sparse-continuous priors. The MSSCR achieves sidelobe suppression without requiring any PSF measurement or estimation and effectively preserving the axial resolution. The experimental results demonstrate that the MSSCR achieves sidelobe suppression of more than 8 dB. We believe that the MSSCR holds potential for addressing sidelobe artifacts in OCT.

A simulation study to evaluate the effect of 2D antiscatter grid primary transmission on flat panel detector based CBCT image quality

Abstact Purpose. Two-dimensional antiscatter grids’ (2D-ASGs) septal shadows and their impact on primary transmission play a critical role in cone-beam computed tomography (CBCT) image noise and artifact characteristics. Therefore, a numerical simulation platform was developed to evaluate the effect of 2D-ASG’s primary transmission on image quality, as a function of grid geometry and CBCT system properties. Methods. To study the effect of 2D-ASG’s septal shadows on primary transmission and CBCT image quality, two new methods were introduced; one to simulate projection signal gradients in septal shadows, and the other to simulate septal shadow variations due to gantry flex. Signal gradients in septal shadows were simulated by generating a system point spread function that was directly extracted from projection images of 2D-ASG prototypes in experiments. Variations in septal shadows due to gantry flex were simulated by generating oversampled shadow profiles extracted from experiments. Subsequently, the effect of 2D-ASG’s septal shadows on primary transmission and image quality was evaluated. Results. For an apparent septal thickness of 0.15 mm, the primary transmission of 2D-ASG varied between 72%–90% for grid pitches 1–3 mm. In low-contrast phantoms, the effect of 2D-ASG’s radiopaque footprint on information loss was subtle. At high spatial frequencies, information loss manifested itself as undersampling artifacts, however, its impact on image quality is subtle when compared to quantum noise. Effects of additive electronic noise and gantry flex induced ring artifacts on image quality varied as a function of grid pitch and septal thickness. Such artifacts were substantially less in lower resolution images. Conclusion. The proposed simulation platform allowed successful evaluation of CBCT image quality variations as a function of 2D-ASG primary transmission properties and CBCT system characteristics. This platform can be potentially used for optimizing 2D-ASG design properties based on the imaging task and properties of the CBCT system.

Influence of Apodization Pupil Function on the Intensity Point Spread Function of Optical System

Apodization is the significant modification of the impulse response of the optical system. This modification plays a vital role in improving the imaging and focusing characteristics foe various optical systems. We present our studies on apodization of pupils with amplitude filter respect to images of point objects . The central intensity distribution, the Full width at half maximum (FWHM)of point spread function, first maxima and first minima are evaluated and compared with and without apodisation .our results shown that the resolution of the intensity of the PSF has been modified as the degree of apodization increases .

Improving the Accuracy of Range Migration in 3-D Near-Field Microwave Imaging

Calibration measurements play a crucial role in improving the accuracy of both qualitative and quantitative microwave imaging. Ideally, in 3-D near-field imaging, a calibration measurement should be performed at each desired range (or depth) position, which can be very time-consuming. An analytical prediction of the range behavior of the resolvent kernel of scattering can reduce the calibration effort to a single measurement at a reference range position. Range-translation (or range-migration) analytical expressions are already widely used in far-zone radar and acoustic imaging; however, their accuracy deteriorates significantly in near-field scenarios. Here, we propose a range-migration technique for near-field microwave imaging with monostatic and bistatic measurement configurations. From a single measurement of the system point-spread function (PSF), the PSF magnitude and phase are accurately predicted at any desired range position. The proposed migration is performed in real space; however, it can also be applied with Fourier-domain (or <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$</tex-math> </inline-formula> -space) inversion methods. Here, it is applied with quantitative microwave holography in simulation-based and experimental examples, which validate its performance and illustrate its limitations.

Single exposure passive three-dimensional information reconstruction based on an ordinary imaging system

Existing three-dimensional (3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imaging system. Using the point spread function of the imaging system to realize the non-coding measurement on the target, the full-focus images and depth information of the 3D target can be extracted from a single two-dimensional (2D) image through the compressed sensing algorithm. Simulation and experiments show that this approach can complete passive 3D imaging based on an ordinary imaging system without any coding operations. This method can achieve millimeter-level vertical resolution under single exposure conditions and has the potential for real-time dynamic 3D imaging. It improves the efficiency of 3D information detection, reduces the complexity of the imaging system, and may be of considerable value to the field of computer vision and other related applications.

Field dipole interaction and polarization effects in light-sheet optical fluorescence microscopy

Polarization plays a crucial role in understanding the interaction of fluorescent molecules in a light field. We report the study on the effect of a field–dipole interaction under polarization light-sheet fluorescence microscopy using the vectorial theory of light. The molecule is suitably modeled as a radiating electric dipole in a polarized electric field (both linear and random), and the system point spread function (PSF) is determined for different orientations of the dipole (both fixed and random). PSF analysis and contour plots suggest distinct nature of a field distribution in each case, indicating the importance of a field–dipole interaction for high-quality fluorescence imaging. The analysis suggests that the field spreads gradually along the polarization axis at a high numerical aperture (NA) of the objective lens, whereas it is more isotropic and homogeneous at low NA. Moreover, fast changes are not observed at low NA (i.e., far from the central lobe in the field contour plots), suggesting the absence of high-frequency components. However, sidelobes are prominent for linear polarized (along x) light. On the other hand, rapid variations are evident for randomly polarized light, depicting the presence of high spatial frequencies in the system optical transfer function. The other significant observation is the distinct frequency spectrum (both kx and ky) for random and fixed dipoles, indicating the significance of dipole orientation in a light-sheet field. Compared to the point-illumination-based fluorescence microscopy, sheet based polarization technique provides a high signal-to-noise ratio, a uniform field, an order large field of view, and critical information (related to the micro-environment of a dipole and its short-range interactions). The study is expected to facilitate polarization-sensitive investigation of large biological specimens (both fixed and live).

Unsupervised Terahertz Image Restoration Based on CycleGan

Terahertz (THz) is considered as one of the key technologies for sixth generation communications, military, medical imaging and industrial inspection. THz images are susceptible to degradation due to system noise and point spread functions during transmission. The existing deep learning methods use ground truth and input images for supervised training that can recover THz images very well. But it’s difficult to obtain labeled THz data in practical application. In this paper, we propose an attentional adversarial cycle generation network for THz image restoration (CycleTHz) based on CycleGan to address this problem. The CycleTHz generates clean images firstly by an attention-guided generation network and then discriminates the quality of the generators by an attention discriminator. In addition, RGB color loss is used for image channels for constraint. To the best of our knowledge, this is the first THz dataset to be trained using an unsupervised approach. Extensive experiments show that the proposed method improves the PSNR and SSIM by 43.4% and 101.7% compared with CycleGan, which is a benchmark method for the unsupervised development in THz image restoration. The code is available at https://github.com/hellogry/UnsupervisedCycleTHz