DiriNet:An Estimation Network for Spectral Response Function and Point Spread Function

Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.

PET image reconstruction with a system matrix containing point spread function derived from single photon incidence response

A point spread function（PSF） for the blurring component in positron emission tomography（PET） is studied. The PSF matrix is derived from the single photon incidence response function. A statistical iterative reconstruction（IR） method based on the system matrix containing the PSF is developed. More specifically, the gamma photon incidence upon a crystal array is simulated by Monte Carlo（MC） simulation, and then the single photon incidence response functions are calculated. Subsequently, the single photon incidence response functions are used to compute the coincidence blurring factor according to the physical process of PET coincidence detection. Through weighting the ordinary system matrix response by the coincidence blurring factors, the IR system matrix containing the PSF is finally established. By using this system matrix, the image is reconstructed by an ordered subset expectation maximization（OSEM） algorithm. The experimental results show that the proposed system matrix can substantially improve the image radial resolution, contrast,and noise property. Furthermore, the simulated single gamma-ray incidence response function depends only on the crystal configuration, so the method could be extended to any PET scanner with the same detector crystal configuration.

Bistatic Synthetic Aperture Radar Point Spread Function Characteristic Analysis

Based on the point spread function （PSF） theory, the side-lobe extension direction of the impulse response in bistatic synthetic aperture radar （BSAR） is analyzed in detail; in addition, the corresponding autofocus in BSAR should be considered along iso-range direction, not the traditional azimuth resolution （AR） direction. The conclusion is verified by the computer simulation.

A Knife-edge Input Point Spread Function Estimation Method for Document Images

In this paper the progress of document image Point Spread Function （PSF） estimation will be presented. At the beginning of the paper, an overview of PSF estimation methods will be introduced and the reason why knife-edge input PSF estimation method is chosen will be explained. Then in the next section, the knife-edge input PSF estimation method will be detailed. After that, a simulation experiment is performed in order to verify the implemented PSF estimation method. Based on the simulation experiment, in next section we propose a procedure that makes automatic PSF estimation possible. A real document image is firstly taken as an example to illustrate the procedure and then be restored with the estimated PSF and Lucy-Richardson deconvolution method, and its OCR accuracy before and after deconvolution will be compared. Finally, we conclude the paper with the outlook for the future work.

Point spread functions for a small gamma camera with pinhole collimator

A set of point spread functions (PSF) has been obtained by means of Monte-Carlo simulation for asmall gamma camera with a pinhole collimator of various hole diameters. The FOV (field of view) of the camera isexpended from 45 mm to 70 mm in diameter. The position dependence of the variances of PSF is presented, and theacceptance for the 140 kev gamma rays is explored. A phantom of 70 mm in diameter was experimentally imaged inthe camera with effective FOV of only 45 mm in diameter.

Physics-constrained deep-inverse point spread function model:toward non-line-of-sight imaging reconstruction

Non-line-of-sight(NLOS)imaging has emerged as a prominent technique for reconstructing obscured objects from images that undergo multiple diffuse reflections.This imaging method has garnered significant attention in diverse domains,including remote sensing,rescue operations,and intelligent driving,due to its wide-ranging potential applications.Nevertheless,accurately modeling the incident light direction,which carries energy and is captured by the detector amidst random diffuse reflection directions,poses a considerable challenge.This challenge hinders the acquisition of precise forward and inverse physical models for NLOS imaging,which are crucial for achieving high-quality reconstructions.In this study,we propose a point spread function(PSF)model for the NLOS imaging system utilizing ray tracing with random angles.Furthermore,we introduce a reconstruction method,termed the physics-constrained inverse network(PCIN),which establishes an accurate PSF model and inverse physical model by leveraging the interplay between PSF constraints and the optimization of a convolutional neural network.The PCIN approach initializes the parameters randomly,guided by the constraints of the forward PSF model,thereby obviating the need for extensive training data sets,as required by traditional deep-learning methods.Through alternating iteration and gradient descent algorithms,we iteratively optimize the diffuse reflection angles in the PSF model and the neural network parameters.The results demonstrate that PCIN achieves efficient data utilization by not necessitating a large number of actual ground data groups.Moreover,the experimental findings confirm that the proposed method effectively restores the hidden object features with high accuracy.

Plasmon point spread functions： How do we model plasmon-mediated emission processes？

A major challenge with studying plasmon-mediated emission events is the small size of plasmonic nanoparticles relative to the wavelength of light. Objects smaller than roughly half the wavelength of light will appear as diffraction-limited spots in far-field optical images, presenting a significant experimental challenge for studying plasmonic processes on the nanoscale. Super-resolution imaging has recently been applied to plasmonic nanosystems and allows plasmon-mediated emission to be resolved on the order of ~5 nm. In super-resolution imaging, a diffraction-limited spot is fit to some model function in order to calculate the position of the emission centroid, which represents the loca- tion of the emitter. However, the accuracy of the centroid position strongly depends on how well the fitting function describes the data. This Perspective discusses the commonly used two-dimensional Gaussian fitting function applied to super-resolution imaging of plasmon-mediated emission, then introduces an alternative model based on dipole point spread flmctions. The two fitting models are compared and contrasted for super-resolution imaging of nanoparticle scattering/luminescence, surface-enhanced Raman scattering, and surface-enhanced fluorescence.

Numerical study of point spread function of a fast neutron radiography system based on scintillating-fiber array

For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.

Point spread function modeling and image restoration for cone-beam CT

X-ray cone-beam computed tomography （CT） has such notable features as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection image degradation and restoration in cone-beam CT, a point spread function （PSF） modeling method is proposed first. The general PSF model of cone- beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection image restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection image restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods.

A phase model for point spread function estimation in ground-based astronomy

In ground-based astronomy, images of objects in outer space are acquired via ground-based tele- scopes. However, the imaging system is generally interfered by atmospheric turbulence and hence images so acquired are blurred with unknown point spread function （PSF）. To restore the observed images, aberration of the wavefront at the telescope＇s aperture, i.e., the phase, is utilized to derive the PSF. However, the phase is not readily available. Instead, its gradients can be collected by wavefront sensors. Thus the usual approach is to use regularization methods to reconstruct high-resolution phase gradients and then use them to recover the phase in high accuracy. Here, we develop a model that reconstructs the phase directly. The proposed model uses the tight frame regularization and it can be solved efficiently by the Douglas-Rachford alternating direction method of multipliers whose convergence has been well established. Numerical results illustrate that our new model is efficient and gives more accurate estimation for the PSF.

Effects of mask-alignment error on point spread function for multi-level Fresnel diffractive lenses

The full aperture complex amplitude transmittance function of a multi-level diffraction lens with mask- alignment errors was derived based on scalar diffraction theory. The point spread function （PSF） was calculated by the Kirchhoff diffraction integral. It is found that the radius of the Airy disk increases with the increase of the error in the direction of misalignment, and the image center shifts along the direction of misalignment. A fourlevel diffractive lens with a diameter of 80 mm was fabricated, and its PSF and diffraction efficiency of ＋1st order were calculated and measured. The distribution of PSF is consistent with the calculated results, and the tested diffraction efficiency is slightly smaller than the calculated value; the relative error is 5.71%.

Resolution enhancement of optical scanning holography with a spiral modulated point spread function

In optical scanning holography, one pupil produces a spherical wave and another produces a plane wave. They interfere with each other and result in a fringe pattern for scanning a three-dimensional object. The resolution of the hologram reconstruction is affected by the point spread function(PSF) of the optical system. In this paper, we modulate the PSF by a spiral phase plate, which significantly enhances the lateral and depth resolution. We explain the theory for such resolution enhancement and show simulation results to verify the efficacy of the approach.

基于显著性区域检测的多尺度图像盲复原算法

针对大多数基于先验的盲图像去模糊算法耗时较长和显著边缘结构提取不理想的问题,提出一种基于显著性区域检测的多尺度图像盲复原算法。为了复原出更加清晰的图像,采用由粗略到精细的多尺度交替迭代框架构建图像金字塔。在图像单一尺度方面,首先提取出图像中具有强边缘结构的显著性区域,并对其施加l_(0)范数约束,提出显著映射先验;将显著性映射先验和最大后验概率相结合并引入传统图像去模糊模型中,构造出点扩散函数估算模型,利用半二次分裂算法解决模型的非凸问题;对点扩散函数进行复原时,利用点扩散函数相似度的变化量限制每个尺度中的过渡迭代;对模糊图像和最终估计的点扩散函数进行非盲解卷积,获得复原图像。实验结果表明:与现有的主流去模糊算法相比,新算法在合成数据集和真实数据集中都可以有效抑制振铃和伪影现象,得到了很好的视觉体验,且评价指标均优于对比算法,同时大大缩减了复原时间。

飞行时间和点扩散函数对18F-FDGPET/CT肺癌纵隔淋巴结转移的增益价值

目的探讨飞行时间(TOF)和点扩散函数(PSF)重建对18F-FDGPET/CT显像肺癌纵隔淋巴结转移的增益价值。资料与方法回顾性分析2020年3月9日—2021年7月23日在佛山市第一人民医院行PET/CT检查的肺癌纵隔淋巴结转移患者68例。分别采用有序子集最大期望值迭代法(OSEM)、OSEM+TOF、OSEM+PSF、OSEM+TOF+PSF重建图像,比较不同重建算法对肺癌纵隔淋巴结转移病灶的分辨能力,以及病灶信噪比(SNR)和标准化摄取值(SUV)的差异。结果使用OSEM+TOF+PSF重建可获得病灶SUVmax、SUVmean和SNR的最高值,与常规OSEM比较分别增加了21.99%、22.86%和60.14%(t=28.321、19.11、11.059,P均<0.01);其差异百分比在直径≤22 mm的较小病灶中明显大于直径>22 mm的较大病灶(24.1%比21.1%、25.3%比19.3%、70.6%比63.3%;Z=-3.658、-4.313、-2.154,P均<0.05),在SNR≤15.31的低对比度病灶中明显大于SNR>15.31的高对比度病灶(23.6%比21.4%、25.3%比21.1%、85.7%比46.0%;Z=-3.519、-2.336、-5.106,P均<0.05);在不同重建算法的病灶可检测性评价结果中,OSEM+TOF+PSF图像对纵隔淋巴结转移病灶的显示最清晰,其中87.4%的病灶为明确存在,显著高于OSEM图像的73.1%(χ^(2)=11.704,P=0.001),但OSEM+PSF图像中病灶明确存在的比例与OSEM比较并未显著增加(73.1%比75.8%;χ^(2)=0.361,P=0.548)。结论TOF和PSF结合能显著提高肺癌纵隔淋巴结转移病灶的探测能力,以及病灶SNR和SUV,尤其在小病灶和低对比度病灶中更为显著。

基于边缘约束与范数比值的图像盲复原

针对现有的研究方法对运动所引起的模糊图像进行复原时效果欠佳的问题,提出一种基于边缘约束与范数比值的图像盲复原算法.该算法首先对退化图像的边缘进行约束,得到图像的强边缘结构,提高了点扩散函数估计的准确率;然后对要估计的清晰图像构造范数比值的稀疏惩罚约束项,并将得到的强边缘信息与构造的范数比值惩罚约束项进行结合用于指引点扩散函数的复原;在对点扩散函数进行复原时,由粗到细多尺度交替迭代估计点扩散函数,使得迭代出的最大尺度更加精确;最后对图像进行非盲解卷积求解,使其复原.该算法将退化图像的边缘信息与构造的范数比值惩罚约束项进行结合指导点扩散函数的复原,可以抑制图像在复原过程中产生的大量伪迹.实验结果表明,该算法对恢复图像边缘细节具有很好的效果,可以得到优质的复原图像.

类THAAD导引头气动光学效应计算研究

针对类美国末段高空域防御(Terminal High Altitude Area Defense,THAAD)系统的红外导引头外形,开展了气动光学效应计算分析,并将其用于飞行器设计。利用国家数值风洞工程高速流场计算软件NNW-HyFLOW,考虑热化学非平衡效应和材料传热耦合效应,对导引头典型状态的流场进行了模拟,获得了流场的密度、温度、压力等参数和窗口的温度场参数。基于流场参数,利用HyFLOW气动光学传输效应计算功能,开展了红外光学传输成像计算;利用HyFLOW气动光学辐射效应计算模块,开展了流场和光学窗口的热辐射计算。计算结果表明,类THAAD导引头在30 km以上飞行时,流场和光学窗口基本不会影响目标信号的光学传输成像,但流场和窗口的热辐射效应会对导引头识别目标造成影响。不过随着飞行高度的升高,这种影响会减小。

基于谱分析的红外成像模糊去除算法研究

针对红外成像中出现的像差和运动模糊问题,提出了一种基于谱分析的红外成像模糊去除算法。该方法通过对模糊问题的分析,利用红外图像频谱信息构建了模糊函数估计方法,通过数据拟合项和正则项的优化,实现红外图像的模糊去除。实验在运动模糊图像数据集和静态像差图像上进行测试,结果表明:在数据集模糊去除实验上,相比之前的方法,本文方法峰值信噪比(PSNR,peak signal-to-noise ratio)提升了2.01 dB,结果相似性(SSIM,structural similarity index)提升了0.06;静态像差图像在实验室条件下通过短波红外探测器采集,算法在主观上有较明显的复原效果,且针对高通量光学系统成像复原效果更为显著。

折反式变形光学系统偏振像差分析及其对点扩散函数的影响

变形光学系统是一种具有双平面对称性的相对特殊的光学系统,其结构会引入非旋转对称的偏振像差。针对这一问题,本文构建一个折反式变形光学系统,并对该系统的偏振像差及其对点扩散函数的影响进行系统分析。基于三维偏振光线追迹对折反式变形光学系统进行仿真计算,获得偏振像差的详细数据,并计算各个表面的二向衰减、相位延迟分布特性以及系统的琼斯瞳、振幅响应矩阵、点扩散函数和偏振串扰对比度。结果表明:最大二向衰减为0.145,最大相位延迟为1.46×10^(-2)rad,均出现在次镜位置。2∶1变形比的光学系统的振幅响应函数在长焦端和短焦端方向的偏振串扰项存在40.6%的差异,偏振串扰将该变形光学系统的对比度限制在10^(-6)量级。高精度变形光学系统中的偏振像差不可忽略,可采用膜层设计和折反式结构等方法降低偏振像差影响。该研究结论可为变形光学系统在深空探测、相干通信系统等领域的设计提供参考。

计算成像技术中的点扩散函数工程

围绕光学成像中点扩散函数(Point spread function,PSF)在计算成像中的新内涵与应用,介绍了传统光学成像中PSF的概念以及PSF在光学系统设计中关键作用,并简要说明了几种利用PSF恢复图像算法以及图像评价指标。在此基础上以计算成像框架下信息传递的视角重新审视了PSF的内涵,从狭义、广义光学系统两个方面对计算成像领域中的相关研究进行了归纳总结,最后展望了PSF工程技术的应用前景及发展趋势。

新一代帕洛马天文台光谱仪的虚拟刀口欠采样像质测量方法

天文光谱仪的成像质量可用点扩散函数或线扩散函数来表征,但其相对于光谱仪探测器通常为欠采样,很难直接测量。在新一代帕洛马天文台光谱仪的像质测试中引入虚拟刀口法进行光源物面扫描,并应用虚拟刀口法开展欠采样光谱仪像质及光源尺度测量,通过模拟和实验研究,对比分析过采样经典直边刀口法和过采样直接测量方法,验证了虚拟刀口法具有良好的测量精度。在693 nm处,直边刀口法测得光谱仪过采样线扩散函数的半高全宽为7.05μm,虚拟刀口法测量欠采样线扩散函数的半高全宽为7.14μm,测量误差为1.3%。在0.3"视场的光源尺度下,虚拟刀口法测得689、693、701 nm欠采样线扩散函数的半高全宽分别为24.2、27.7、30.8μm,以过采样直接测量结果为参考,其测量准确度分别为98.3%,93.9%和88.8%。实验结果表明,探测器成像严重欠采样时,采用光源物面扫描的虚拟刀口法可准确测量光谱仪的成像质量,该方法结合色散系数还可实现光谱仪分辨率的测量,相关研究工作可为天文光谱仪像质的直接测量提供借鉴。