Simulated Point Spread Function Research Articles

Beyond synthetic aperture focusing: deconvolution-based elevation resolution enhancement using simulated point spread function for linear array-based three-dimensional photoacoustic imaging.

This paper introduces a deconvolution-based method to enhance the elevation resolution of a linear array-based three-dimensional (3D) photoacoustic (PA) imaging system. PA imaging combines the high contrast of optical imaging with the deep, multi-centimeter spatial resolution of ultrasound (US) imaging, providing structural and functional information about biological tissues. Linear array-based 3D PA imaging is easily accessible and applicable for ex vivo studies, small animal research, and clinical applications in humans. However, its elevation resolution is limited by the acoustic lens geometry, which establishes a single elevation focus. Previous work used synthetic aperture focusing (SAF) to enhance elevation resolution, but the resolution achievable by SAF is constrained by the size of the elevation focus. Here, we introduce the application of Richardson-Lucy deconvolution, grounded in simulated point-spread-functions, to surpass the elevation resolution attainable with SAF alone. We validated this approach using both simulation and experimental data, demonstrating that the full-width-at-half-maximum of point targets on the elevation plane was reduced compared to using SAF only, suggesting resolution improvement. This method shows promise for improving 3D image quality of existing linear array-based PA imaging systems, offering potential benefits for disease diagnosis and monitoring.

Investigation of Numerical Simulation for Adaptive Optics System

In this study, the performance of the adaptive optics (AO) system was analyzed through a numerical computer simulation implemented in MATLAB. Making a phase screen involved turning computer-generated random numbers into two-dimensional arrays of phase values on a sample point grid with matching statistics. Von Karman turbulence was created depending on the power spectral density. Several simulated point spread functions (PSFs) and modulation transfer functions (MTFs) for different values of the Fried coherent diameter (ro) were used to show how rough the atmosphere was. To evaluate the effectiveness of the optical system (telescope), the Strehl ratio (S) was computed. The compensation procedure for an AO system was implemented. Analytical analysis was used to define the wave front and aberrations of the circular aperture telescope. Zernike polynomials were used to describe the residual error and figure out how much the compensation changed the measured turbulence values. The results of the computer simulation involving atmospheric turbulence reveal that elevating the ro values (4, 8, 12, 16, 20, 24, 28, 32) cm resulted in a 3.4% rise in S. However, when the adaptive optics system operated with a constant ro (20 cm), augmenting the Zernike aberration modes led to a remarkable 44% increase in S, signifying a substantial enhancement in the compensation procedure.

The Chromatic Point-spread Function of Weak Lensing Measurement in the Chinese Space Station Survey Telescope

Weak gravitational lensing is a powerful tool in modern cosmology. To accurately measure the weak lensing signal, one has to control the systematic bias on a small level. One of the most difficult problems is how to correct the smearing effect of the Point-Spread Function (PSF) on the shape of the galaxies. The chromaticity of PSF for a broad-band observation can lead to new subtle effects. Since the PSF is wavelength-dependent and the spectrum energy distributions between stars and galaxies are different, the effective PSF measured from the star images will be different from those that smear the galaxies. Such a bias is called color bias. We estimate it in the optical bands of the Chinese Space Station Survey Telescope from simulated PSFs, and show the dependence on the color and redshift of the galaxies. Moreover, due to the spatial variation of spectra over the galaxy image, another higher-order bias exists: color gradient bias. Our results show that both color bias and color gradient bias are generally below 0.1% in CSST. Only for small-size galaxies, one needs to be careful about the color gradient bias in the weak lensing analysis using CSST data.

Miniature color camera via flat hybrid meta-optics.

The race for miniature color cameras using flat meta-optics has rapidly developed the end-to-end design framework using neural networks. Although a large body of work has shown the potential of this methodology, the reported performance is still limited due to fundamental limitations coming from meta-optics, mismatch between simulated and resultant experimental point spread functions, and calibration errors. Here, we use a HIL optics design methodology to solve these limitations and demonstrate a miniature color camera via flat hybrid meta-optics (refractive + meta-mask). The resulting camera achieves high-quality full-color imaging for a 5-mm aperture optics with a focal length of 5 mm. We observed a superior quality of the images captured by the hybrid meta-optical camera compared to a compound multi-lens optics of a mirrorless commercial camera.

Hybrid diffractive optics design via hardware-in-the-loop methodology for achromatic extended-depth-of-field imaging.

End-to-end optimization of diffractive optical elements (DOEs) profile through a digital differentiable model combined with computational imaging have gained an increasing attention in emerging applications due to the compactness of resultant physical setups. Despite recent works have shown the potential of this methodology to design optics, its performance in physical setups is still limited and affected by manufacturing artefacts of DOE, mismatch between simulated and resultant experimental point spread functions, and calibration errors. Additionally, the computational burden of the digital differentiable model to effectively design the DOE is increasing, thus limiting the size of the DOE that can be designed. To overcome the above mentioned limitations, a co-design of hybrid optics and image reconstruction algorithm is produced following the end-to-end hardware-in-the-loop strategy, using for optimization a convolutional neural network equipped with quantitative and qualitative loss functions. The optics of the imaging system consists on the phase-only spatial light modulator (SLM) as DOE and refractive lens. SLM phase-pattern is optimized by applying the Hardware-in-the-loop technique, which helps to eliminate the mismatch between numerical modelling and physical reality of image formation as light propagation is not numerically modelled but is physically done. Comparison with compound multi-lens optics of a last generation smartphone and a mirrorless commercial cameras show that the proposed system is advanced in all-in-focus sharp imaging for a depth range 0.4-1.9 m.

The point spread function reconstruction – II. The smooth PCA

ABSTRACT Accurate shear measurement is a key topic in weak lensing community. Point spread function (PSF), which smears the observed galaxy image, plays one of the main roles in the systematic errors in shear measurement and must be treated carefully to avoid bias and errors in cosmological parameters. In this paper, we present new PSF measurement methods, Smooth-PCA (SPCA) and Improved-SPCA (iSPCA), which can reconstruct smooth PSFs with high efficiency. Our methods decompose the star images into smooth principal components by using the Expectation-Maximization-PCA (EMPCA) method, and the smooth principal components are composed by Moffatlets basis functions, which are derived from the Moffat function. We demonstrate our approaches based on simulated Moffat PSFs and phosim star images. The constructed smooth principal components show flexible and efficient as the same as EMPCA, and have more stable patterns than EMPCA under noises contamination. We then check the reconstruction accuracy on the shape of PSFs. We find that our methods are able to reconstruct the PSFs at the same precision as the EMPCA method that indicates and iSPCA are promising for weak lensing shear measurement.

A Deep Transfer Learning Model for Packaged Integrated Circuit Failure Detection by Terahertz Imaging

Terahertz time-domain spectroscopy imaging system (THz-TDS) is becoming a promising tool for packaged integrated circuit (IC) failure detection due to its nonmetal penetrability and low radiation. However, two major obstacles are hindering the industrial application of the THz-TDS based IC detection method: 1) the low resolution of THz images may affect the detection accuracy; 2) the failure detection tasks are always carried out manually, which is inefficient and inaccurate. Thus, in this paper, we firstly enhanced the quality of IC THz images with a deconvolution algorithm and a mathematically simulated point spread function (PSF), and then we proposed a deep convolutional neural network (CNN) based failure detection framework to achieve end-to-end IC inspection automatically. Besides, we introduced transfer learning to overcome the limitation of the IC dataset size. The result demonstrated that our proposed method achieved excellent performance concerning both accuracy and efficiency.

Self-aligned fiber-based dual-beam source for STED nanolithography

A fiber-based source that can be exploited in a stimulated emission depletion (STED) inspired nanolithography setup is presented. Such a source maintains the excitation beam pulse, generates a ring-shaped depletion beam, and automatically realizes dual-beam coaxial alignment that is critical for two beam nanolithography. The mode conversion of the depletion beam is realized by using a customized vortex fiber, which converts the Gaussian beam into a donut-shaped azimuthally polarized beam. The pulse width and repetition frequency of the excitation beam remain unchanged, and its polarization states can be controlled. According to the simulated point spread function of each beam in the focal region, the full width at half-maximum of the effective spot size in STED nanofabrication could decrease to less than 28.6 nm.

Image restoration of high-energy X-ray radiography with a scintillator blur model

High-energy X-ray radiographic image restoration is performed using a simulated radiation point spread function and an experimentally derived optical point spread function. It is shown that a robust method for removal of thick monolithic scintillator blur can be determined through independent examination of the blur components. We show that the scintillator blur for a 20 MeV end-point X-ray beam and 20 mm thick LYSO scintillator contributes significantly to the system blur. It is also shown that the optical scatter in the monolithic crystal degrades the low-frequency response of the system. The use of a simulated point spread function for image restoration using deconvolution provides a simple method for image restoration, thereby enhancing feature identification and areal density reconstruction.

Simulated reflectance spectra and point spread functions in database constructed by moderate grouping of nine layers in skin model

This paper presents a numerical study on simulated spectra and point spread functions in the database that we constructed by moderate grouping of nine layers in a skin model. The database is used for identification of a simulated skin reflectance spectrum which seems most closed to a certain target spectrum or a measured spectrum. On the basis of the properties of absorption and scattering coefficients in a nine-layered skin tissue model, we classify nine layers into two and three groups for changing values of the absorption and scattering coefficients, respectively, and then reflectance spectra are simulated by Monte Carlo method with these five groups to build reflectance spectral database. The desired spectrum is extracted from the database by using the root mean square error. To identify uniquely the most desirable spectrum among some similar spectra contained in the database, we propose additionally the use of a point spread function of reflected intensity on the skin surface. Simulated results demonstrate that this approach is promising to identify the most likely spectrum that is fit to the target spectrum. The finally identified spectrum in the database gives its absorption and scattering coefficients in each of the nine layers which are used to estimate skin conditions.

Physics-based model of the adaptive-optics-corrected point spread function

Context.Adaptive optics (AO) systems greatly increase the resolution of large telescopes, but produce complex point spread function (PSF) shapes, varying in time and across the field of view. The PSF must be accurately known since it provides crucial information about optical systems for design, characterization, diagnostics, and image post-processing.Aims.We develop here a model of the AO long-exposure PSF, adapted to various seeing conditions and any AO system. This model is made to match accurately both the core of the PSF and its turbulent halo.Methods.The PSF model we develop is based on a parsimonious parameterization of the phase power spectral density, with only five parameters to describe circularly symmetric PSFs and seven parameters for asymmetrical ones. Moreover, one of the parameters is the Fried parameterr0of the turbulence’s strength. This physical parameter is an asset in the PSF model since it can be correlated with external measurements of ther0, such as phase slopes from the AO real time computer (RTC) or site seeing monitoring.Results.We fit our model against end-to-end simulated PSFs using the OOMAO tool, and against on-sky PSFs from the SPHERE/ZIMPOL imager and the MUSE integral field spectrometer working in AO narrow-field mode. Our model matches the shape of the AO PSF both in the core and the halo, with a relative error smaller than 1% for simulated and experimental data. We also show that we retrieve ther0parameter with sub-centimeter precision on simulated data. For ZIMPOL data, we show a correlation of 97% between ourr0estimation and the RTC estimation. Finally, MUSE allows us to test the spectral dependency of the fittedr0parameter. It follows the theoreticalλ6/5evolution with a standard deviation of 0.3 cm. Evolution of other PSF parameters, such as residual phase variance or aliasing, is also discussed.

Incoherent holographic camera based on Michelson Interferometer

Incoherent holography is a hybrid imaging technology with coherent and incoherent processes. Compared with coherent holography, incoherent holography can alleviate coherent noise and speckle noise, and thus achieve higher signal-to-noise ratio. In this article, the incoherent holographic camera based on Michelson interferometer is built, which consists of a telescope, a beam-splitting cube, two plane mirrors, two lenses and a monochromatic charge coupled device. The point spread function (PSF) of the system is determined for the first time according to the Fresnel diffraction theory. Both the simulated and experimental 2D PSFs are coincident with each other. The three-step generalized phase shift interferometry instead of the piezo-actuator is used to eliminate zero-order and twin images. The two one-jiao coins with 15 mm apart and a toy house are recorded under xenon lamp illumination. The reconstructed image clearly demonstrates that the system has the ability to obtain spatial 3D information of an object.

Efficient Frequency-Domain Synthetic Aperture Focusing Techniques for Imaging With a High-Frequency Single-Element Focused Transducer

Synthetic aperture focusing techniques (SAFT) make the spatial resolution of the conventional ultrasound imaging from a single-element focused transducer more uniform in the lateral direction. In this work, two new frequency-domain (FD-SAFT) algorithms are proposed, which are based on the synthetic aperture radar's wavenumber algorithm, and 2-D matched filtering technique for the image reconstruction. The first algorithm is the FD-SAFT virtual source (FD-SAFT-VS) that treats the focus of a focused transducer as a virtual source having a finite size and the diffraction effect in the far-field is taken into consideration in the image reconstruction. The second algorithm is the FD-SAFT deconvolution (FD-SAFT-DE) that uses the simulated point spread function of the imaging system as a matched filter kernel in the image reconstruction. The performance of the proposed algorithms was studied using a series of simulations and experiments, and it was compared with the conventional B-mode and time-domain SAFT (TD-SAFT) imaging techniques. The image quality was analyzed in terms of spatial resolution, sidelobe level, signal-to-noise ratio (SNR), contrast resolution, contrast-to-speckle ratio, and ex vivo image quality. The results showed that the FD-SAFT-VS had the smallest spatial resolution and FD-SAFT-DE had the second smallest spatial resolution. In addition, FD-SAFT-DE had generally the largest SNR. The computation run time of FD-SAFT-VS and FD-SAFT-DE, depending on the image size, was lower by 4 to 174 times and 4 to 189 times, respectively, compared to the TD-SAFT-virtual point source.

Optimal PSF Estimation for Simple Optical System Using a Wide-Band Sensor Based on PSF Measurement.

Simple optical system imaging is a method to simplify optical systems by removing aberrations using image deconvolution. The point spread function (PSF) used in deconvolution is an important factor that affects the image quality. However, it is difficult to obtain optimal PSFs. The blind estimation of PSFs relies heavily on the information in the image. Measured PSFs are often misused because real sensors are wide-band. We present an optimal PSF estimation method based on PSF measurements. Narrow-band PSF measurements at a single depth are used to calibrate the optical system; these enable the simulation of real lenses. Then, we simulate PSFs in the wavelength pass range of each color channel all over the field. The optimal PSFs are computed according to these simulated PSFs. The results indicated that the use of the optimal PSFs significantly reduces the artifacts caused by misuse of PSFs, and enhances the image quality.

Automated clustering method for point spread function classification

The point spread function (PSF) plays a very important part in image post-processing and high-precion astrometry and photometry. It is necessary to analyse the properties of the PSF before we use it to process data. However, in real observations, the PSF is affected by many different factors and the shape of it has inevitable spatial and temporal variations that can be hard to describe. In this paper, we propose a clustering method to evaluate the shape variations of PSFs. We analyse the performance of this method with simulated PSFs under different observation conditions. Then, we process two observational data sets with this method. The PSF clustering results can provide a reference for checking observation conditions and can be used for astrometry based on PSF fitting. In general, our method can reveal the morphologic similarities of different PSFs and can provide a reference for observations. The cluster revealed by our method can provide a reference for the evaluation of observation conditions and for the post-processing of astronomical observation data.

Weak Lensing Study in VOICE Survey II: Shear Bias Calibrations

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical $ugri$ imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg$^2$ down to $r_\mathrm{AB}$$\sim$26 mag. In the companion paper by Fu et al. (2018), we present the weak lensing shear measurements for $r$-band images with seeing $\le$ 0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function (PSF) and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of $\sim$3.0%. We study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of $\sim$0.3%. Further analysis shows that galaxies with lower signal-to-noise ratio (SNR) are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighboring galaxies, we find that although most have been rejected in the shape measurement procedure, about one third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to $\sim$0.2% of the multiplicative bias. Such a bias can be removed by further eliminating these neighboring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys.

Multiline 3D beamforming using micro-beamformed datasets for pediatric transesophageal echocardiography

Until now, no matrix transducer has been realized for 3D transesophageal echocardiography (TEE) in pediatric patients. In 3D TEE with a matrix transducer, the biggest challenges are to connect a large number of elements to a standard ultrasound system, and to achieve a high volume rate (>200 Hz). To address these issues, we have recently developed a prototype miniaturized matrix transducer for pediatric patients with micro-beamforming and a small central transmitter. In this paper we propose two multiline parallel 3D beamforming techniques (µBF25 and µBF169) using the micro-beamformed datasets from 25 and 169 transmit events to achieve volume rates of 300 Hz and 44 Hz, respectively. Both the realizations use angle-weighted combination of the neighboring overlapping sub-volumes to avoid artifacts due to sharp intensity changes introduced by parallel beamforming. In simulation, the image quality in terms of the width of the point spread function (PSF), lateral shift invariance and mean clutter level for volumes produced by µBF25 and µBF169 are similar to the idealized beamforming using a conventional single-line acquisition with a fully-sampled matrix transducer (FS4k, 4225 transmit events). For completeness, we also investigated a 9 transmit-scheme (3 × 3) that allows even higher frame rates but found worse B-mode image quality with our probe. The simulations were experimentally verified by acquiring the µBF datasets from the prototype using a Verasonics V1 research ultrasound system. For both µBF169 and µBF25, the experimental PSFs were similar to the simulated PSFs, but in the experimental PSFs, the clutter level was ~10 dB higher. Results indicate that the proposed multiline 3D beamforming techniques with the prototype matrix transducer are promising candidates for real-time pediatric 3D TEE.

Optimized linear wavenumber spectrometer based spectral-domain optical coherence tomography system

In spectraldomain optical coherence tomography the sample is illuminated by a broadband light source, and the spectrum of the interference light between the light returned from the sample and a reference mirror is detected by a grating spectrometer. Conventionally, the grating spectrometer is comprised of a diffraction grating, a focusing lens, and a line-scan camera. According to the grating equation the diffraction angle from the grating is approximately linearly related to the optical wavelength. Thus the distribution function of the light spectrum at the line-scan camera is nonlinearly dependent on wavenumber. For the high-quality image reconstruction, the numerical resampling of the spectral interference data from wavelength-space to wavenumber-space is commonly required prior to the Fourier Transformation. The nonlinear detection of the spectral interferograms in wavenumber space also degrades the depth-dependent signal sensitivity in conventional linear-wavelength spectrometer based spectraldomain optical coherence tomography. Recently reported spectraldomain optical coherence tomography based on a linearwavenumber spectrometer does not need the resampling or interpolating of the nonlinearwavenumber interference spectral data, which greatly reduces the cost of computation and improves the imaging sensitivity. Various methods based on the different evaluation protocols for optimizing the design of the linear-wavenumber spectrometer have been reported. Here we report an effective optimization method for linear-wavenumber spectrometer used in a high-resolution spectral domain optical coherence tomography system. We take the reciprocal of the fullwidthhalfmaximum of the simulated point spread function as an evaluating criterion to optimize the structure parameters of the linearwavenumber spectrometer, including the refractive index and the vertex angle of the dispersive prism and the rotation angle between the diffraction grating and the dispersive prism. According to the optimization, an F2 equilateral dispersive prism is used to construct the optimized linearwavenumber spectrometer with a rotation angle of 21.8°. We construct an optimized linearwavenumber spectrometer and implement the spectrometer in a developed spectraldomain optical coherence tomography system as a detection unit. We evaluate the performances of the linear-wavenumber spectrometer both theoretically and experimentally. The experimentally measured axial resolution of the spectraldomain optical coherence tomography system based on the linear-wavenumber spectrometer is 8.52 μm, and the sensitivity is measured to be 91 dB with -6 dB sensitivity roll-off within a depth range of 1.2 mm. The experimentally measured sensitivity roll-off curve accords well with the theoretical sensitivity roll-off curve. Utilizing the general parallel computing capability of a GPU card, the highquality spectraldomain optical coherence tomography images of the human finger skin can be reconstructed in real time without any resampling or interpolating process.

Acoustic Imaging of In-Duct Aeroengine Noise Sources Using Rotating Beamforming and Phased Arrays

An in-duct rotating beamforming technique, using a wall-mounted array of microphones placed within a long duct, was developed for locating broadband noise sources from an aeroengine fan. The technique was experimentally implemented at the recently constructed long-duct low-speed fan rig test facility at the University of Sao Paulo in Brazil. The test rig has a 16-bladed fan rotor and 14-vaned stator, with speed up to 4250 r/min and a maximum 0.1 Mach number mean axial flow speed. Here, we describe the beamforming details with an emphasis on the mandatory coordinate change to a rotating reference frame for a frequency domain virtual rotating microphone technique. Example sound source maps are presented revealing clear noise blade signatures together with simulated point spread function maps using modal steering vectors at six different frequencies that characterize the beamformer.

Point Spread Function Field Learning Based on Optimal Transport Distances

In astronomy, observing large fractions of the sky within a reasonable amount of time implies using large field-of-view optical instruments that typically have a spatially varying point spread function (PSF). Depending on the scientific goals, galaxy images need to be corrected for the PSF, whereas no direct measurement of the PSF is available. Given a set of PSFs observed at random locations, we want to estimate the PSFs at galaxies locations for shape measurement correction. We propose an interpolation framework based on sliced optimal transport. A nonlinear dimension reduction is first performed based on local pairwise approximated Wasserstein distances. A low dimensional representation of the unknown PSFs is then estimated, which in turn is used to derive representations of those PSFs in the Wasserstein metric. Finally, the interpolated PSFs are calculated as approximated Wasserstein barycenters. The proposed method was tested on simulated monochromatic PSFs of the Euclid space mission telescope (to b...