Image defocus deblurring method based on gradient difference of boundary neighborhood

Background For static scenes with multiple depth layers,existing defocused image deblurring methods have the problems of edge-ringing artifacts or insufficient deblurring owing to inaccurate estimation of the blur amount,and prior knowledge in nonblind deconvolution is not strong,which leads to image detail recovery challenges.Methods To this end,this study proposes a blur map estimation method for defocused images based on the gradient difference of the boundary neighborhood,which uses the gradient difference of the boundary neighborhood to accurately obtain the amount of blurring,thereby preventing boundary ringing artifacts.The obtained blur map is then used for blur detection to determine whether the image needs to be deblurred,thereby improving the efficiency of deblurring without manual intervention and judgment.Finally,a nonblind deconvolution algorithm was designed to achieve image deblurring based on the blur amount selection strategy and sparse prior.Results Experimental results showed that our method improves PSNR(Peak Signal-to-Noise Ratio)and SSIM(Structural Similarity Index)by an average of 4.6%and 7.3%,respectively,compared to existing methods.Conclusions Experimental results showed that the proposed method outperforms existing methods.Compared to existing methods,our method can better solve the problems of boundary ringing artifacts and detail information preservation in defocused image deblurring.

Blurred Defocused Image Restoration Based on FRFT

A technique for restoring the blurred image resulted from defocusing of the lens is proposed in this paper, which is based on fractional Fourier transform （FRFT）.The FRFT, as a powerful tool for the analysis of time-varying signals, is closely connected with the optical imaging system. FRFT also can describe optical imaging process just like Fresnel diffractions, so a defocused imaging model based on FRFT is established to explain the blur phenomena of defocusing image. The defocused imaging model is greatly different from the traditional point spread function （PSF） model, and enables to uncover the blur nature of non-focus image. Then, an image restoration method using the novel model is proposed to handle the blurred defocused image. The method adopted a new iterative phase retrieval approach which can approximately estimate phase signals from intensity signals of a single defocused image by means of FRFT. Restoring image may acquire sharp image by implementing inverse FRFT on complex image signal made from the estimated phase signals and intensity signals. Experimental results demonstrate that the method is effective in restoring blurred defocused image.

Analysis of inverse synthetic aperture radar imaging in the presence of time-varying plasma sheath

The plasma sheath can induce radar signal modulation,causing not only ineffective target detection,but also defocusing in inverse synthetic aperture radar(ISAR)imaging.In this paper,through establishing radar echo models of the reentry object enveloped with time-varying plasma sheath,we simulated the defocusing of ISAR images in typical environment.Simulation results suggested that the ISAR defocusing is caused by false scatterings,upon which the false scatterings’formation mechanism and distribution property are analyzed and studied.The range of false scattering correlates with the electron density fluctuation frequency.The combined value of the electron density fluctuation and the pulse repetition frequency jointly determines the Doppler of false scattering.Two measurement metrics including peak signal-to-noise ratio and structural similarity are used to evaluate the influence of ISAR imaging.

Geometric Calibration and Image Quality Assessment of High Resolution Dual-Camera Satellite

The evaluation of geometric calibration accuracy of high resolution satellite images has been increasingly recognized in recent years.In order to evaluate geometric accuracy for dual-camera satellite images based on the ground control points(GCP),a rigorous geometric imaging model,which was based on the collinear equation of the probe directional angle and the optimized tri-axial attitude determination(TRIAD)algorithm,is presented.Two reliable test fields in Tianjin and Jinan(China)were utilized for geometric accuracy validation of Pakistan Remote Sensing Satellite-1.The experimental results demonstrate a certain deviation of the on-orbit calibration result from the initial design values of the calibration parameters.Therefore,on-orbit geometric calibration is necessary for optical satellite imagery.Within this research,the geometrical performances including positioning accuracy without/with GCP and band registration of the dual-camera satellite were analyzed in detail,and the results of geometric image quality are assessed and discussed.As a result,it is feasible and necessary to establish such a geometric calibration model to evaluate the geometric quality of dual-camera satellite.

基于离焦模糊参数估计的晶圆离焦图像复原

通过高分辨率晶圆离焦图像获得点扩散函数的离焦模糊参数存在计算量大,复原效率低等问题,为此提出了一种基于光斑图像计算离焦模糊参数的晶圆离焦图像复原方法。首先,对光斑图像进行灰度投影,获取线扩散函数曲线;其次,对线扩散函数曲线进行拟合校正,以获得离焦模糊参数,从而确定点扩散函数;最后,采用二次维纳滤波算法对晶圆离焦图像进行复原。实验结果表明,所提出的估计离焦模糊参数的二次维纳滤波方法对晶圆离焦图像进行复原,能够显著提高晶圆离焦图像的峰值信噪比(PSNR),至少提升了0.74 dB,减轻晶圆离焦图像的模糊程度,突显出图像的细节信息,并且计算量小,从而提高复原效率。

Detection of Site-dependent Segmental Mobility of Polymer by Fluorescent Defocused Imaging

Polymer chain ends play an important role in the glassy dynamics of polymeric materials. In this study, a combination of single molecule defocus fluorescence microscopy and well-controlled atom transfer radical polymerization was used to investigate site-dependent segmental mobility of poly（n-butyl methacrylate）. As the temperature increased, the rotation of fluorophores, which were selectively labelled in chain end and chain middle, was gradually activated. The power spectra of rotation trajectories, the distribution of angular displacement as well as the population of rotating fluorophores demonstrated that the local dynamics was more activated at the chain ends than the middles, showing the unique contribution of the chain end to the dynamics of the system.

Fuzzy Based Hybrid Focus Value Estimation for Multi Focus Image Fusion

Due to limited depth-of-field of digital single-lens reflex cameras,the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred(out-of-focus)in the image.Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene.In this paper,a new Fuzzy Based Hybrid Focus Measure(FBHFM)for multi-focus image fusion has been proposed.Optimal block size is very critical step for multi-focus image fusion.Particle Swarm Optimization(PSO)algorithm has been used to find optimal size of the block of the images for extraction of focus measure features.After finding optimal blocks,three focus measures Sum of Modified Laplacian,Gray Level Variance and Contrast Visibility has been extracted and combined these focus measures by using intelligent fuzzy technique.Fuzzy based hybrid intelligent focus values were estimated using contrast visibility measure to generate focused image.Different sets of multi-focus images have been used in detailed experimentation and compared the results with state-of-the-art existing techniques such as Genetic Algorithm(GA),Principal Component Analysis(PCA),Laplacian Pyramid discrete wavelet transform(DWT),and aDWT for image fusion.It has been found that proposed method performs well as compare to existing methods.

Study on Focusing of Area Array Camera by Using Frequency of Images

Focusing of an area array camera is an important step in making a high precision imaging camera. Its testing method needs special study. In this paper, a method of camera focusing is introduced. The defocusing depth of camera is calculated by using the frequency spectrum of defocused image. This method is especially suitable for the focusing of the Planar Array Camera, and avoids the complicated work of adjusting the focus plane of the planar array camera in the focusing process.

利用离焦光斑的离轴望远镜失调校正方法研究

离轴反射式望远镜主要应用于空间天文观测等领域。离轴两反望远镜的成像质量对镜片的失调敏感,且在工作环境下失调后使用激光干涉仪进行校准较为困难。针对这一难题,本文提出了一种利用系统对无穷远点目标的离焦光斑图并使用Swin-Transformer网络计算次镜横向失调量的方法。通过理论计算分析,可以避免多解问题的相机离焦位置,并利用仿真探究了不同离焦量对校正精度的影响,最后搭建实验平台进行验证,训练好的网络使用失调系统的一帧离焦光斑图便可进行失调量的估计。仿真分析与实验结果均验证了该方法的有效性,可实现工作环境中失调望远镜系统的高精度和快速校正。

等离子鞘套下空间高速目标逆合成孔径雷达距离像散焦补偿算法

针对等离子鞘套包覆空间高速目标ISAR成像时出现距离维散焦问题,开展了等离子鞘套包覆空间高速目标ISAR像距离维散焦机理及补偿算法研究。通过分析等离子鞘套的高速流场分布特性,建立了等离子鞘套包覆空间高速目标的回波模型,通过分析回波信号解线调频处理后的相位解析式,揭示了等离子鞘套流场速度的非均匀分布导致ISAR像距离维散焦的机理。为了实现距离维的散焦抑制,采用分数阶傅里叶变换法对等离子鞘套的耦合速度进行估计,构建了相位补偿因子消除等离子鞘套的影响,最终获得了等离子鞘套包覆下空间高速目标的ISAR距离维可靠成像。最后基于流场数据仿真验证了该算法的有效性。

Estimation of particle depth from two defocused images using the Fourier transform

Depth from defocus is one technology for depth estimation.We estimate particle depth information from two defocused images captured simultaneously by two coaxial cameras with different imaging distances.The images are processed with the Fourier transform to obtain the characteristic parameter(i.e.,the standard deviation of the relative blur kernel of these two defocused images).First,we theoretically analyze the functional relationship between the object depth and the standard deviation or variation of the relative blur kernel.Then,we verify the relationship experimentally.We analyze the influence of particle size,window size and image noise on the calibration curves using both numerical simulations and experiments.We obtain the depth range and accuracy of this measurement system experimentally.For the verification experiments,we use a sample of glass microbeads and the irregularly-shaped dust particles on a microscope slide.Both of these experiments present a suitable depth measurement result.Finally,we apply the measuring system to the depth estimation of drops from a small anti-fogging spray.The results show that our system and image processing algorithm are robust for different types of particles,facilitating the in-line three-dimensional positioning of particles.

基于单目视觉边缘频谱的散焦图像测距算法研究

为了实现基于单目相机的弱或无表面纹理特征目标精确测距,提出了一种基于保留边缘频谱信息的改进散焦图像测距算法。通过对比以傅立叶变换和拉普拉斯变换为计算核心的两种经典散焦测距理论,构建相应的清晰度评价函数,根据灵敏度更好的频谱清晰度函数选择基于频谱的散焦测距法,并根据频谱清晰度函数在保留目标边缘信息的基础上选择频域计算范围,从而进行测距。为验证算法的可行性,本文采用6组不同的鸭蛋样本,获取不同光圈、不同距离的散焦图像,利用该改进算法求解鸭蛋到相机镜头的距离。实验结果表明,基于边缘频谱保留的散焦图像测距改进算法具有良好的测距效果,相关系数为0.986,均方根误差为11.39 mm,并发现对于斜放拍摄的鸭蛋图像进行图像旋转处理后,可有效地提升测距能力,均方根误差从11.39 mm下降至8.76 mm,平均相对误差从2.85%下降至2.28%,相关系数提升至0.99。基本满足了弱或无表面纹理特征目标测距的稳定、精度等要求。

多聚焦图像离焦模糊区域的SIFT特征提取

常规的尺度不变特征变换(SIFT)图像特征提取方法难以提取多聚焦图像离焦模糊区域的特征,使得图像间存在局部、少量的公共特征,导致多聚焦图像配准精度差,严重影响后续图像融合和三维重建质量。在分析图像离焦模糊区域特征提取不确定性的基础上,提出了一种多聚焦图像离焦模糊区域的SIFT特征提取方法。首先提取多聚焦图像聚焦清晰区域的SIFT特征,再利用光流跟踪提取对应离焦模糊区域的SIFT特征,避免了在离焦模糊区域直接提取SIFT特征的不确定性。实验结果表明:提出的方法在离焦模糊区域具有良好的SIFT特征提取能力和提取精度,能实现多聚焦图像SIFT特征匹配数量显著增长,SIFT特征提取的误差为0.03~0.39 pixels,优于现有方法的0.21~1.71 pixels。降低了离焦模糊区域SIFT特征提取的不确定性,为多聚焦图像精确配准奠定了基础。

一种基于参考图频谱相关的模糊参数判别方法

对于模糊图像的复原,模糊模型参数判别的准确性是一关键,针对大尺度模糊图像有效细节信息的丢失,噪声等干扰对模型特征的减弱,以及实拍图像的频谱特征不明显等问题,提出了一种基于参考图像频谱相关性的模糊参数判别方法,将一幅清晰图像按照不同模糊参数进行模糊处理,并与待复原图的频谱进行相关性分析计算,以获得准确的模型参数。实验结果证明,该方法能够适应大尺度散焦模糊,具有较强的抗噪性并且适应实拍的散焦模糊图像复原。

基于梯度及HVS特性的离焦模糊图像质量评价

在当前人眼视觉系统(HVS)特性研究的基础上提出基于梯度及HVS特性的离焦模糊图像质量评价模型(GVSSIM)。该模型利用Sobel边缘梯度算子提取图像的梯度信息,并根据人眼视觉特性进行视觉加权,得到新的结构相似性评价指标,进而获得图像质量评价指标。该方法与SSIM(图像结构相似度)评价模型相比,具有计算简单的特点,对离焦模糊图像的评价结果能更好地反映人眼视觉感受。

泰伯效应对激光并行共焦显微系统成像影响的研究

激光并行共焦显微系统采用微透镜阵列作为分光器件,将会不可避免地引入泰伯效应,造成沿光轴方向的多次成像。形成的这些像面中有且只有一个是正焦像面,它不仅没有边缘效应、能量更加集中,而且可以有效提高系统的测量分辨率。如何寻找正焦像面是削弱泰伯效应对测量影响的关键。实验中发现,通过增大微透镜阵列光栅常数可以增大泰伯距离,从而减弱离焦像面对测量的影响;并且设计了一种识别正、离焦像面的方法,能够准确找到正焦像面,保证了系统的测量分辨率。

基于离焦星点图的RC式望远镜装调技术

为了实现大口径望远镜的装调,基于离焦星点图的图像处理和分析,研究了RC式望远镜的装调技术。首先,根据横向几何像差分析离焦像点图像和系统装调误差之间的关系,重点讨论了横向误差中离心和倾斜导致的偏心彗差和内外轮廓圆的圆心位置偏离距离的关系,以及彗差消除后残余的像散导致外轮廓椭圆的偏心率随长轴增大而逐渐减小的特点。然后,分析了主次镜之间纵向误差导致的球差和最小圆半径大小的关系。最后,应用Zemax建模仿真验证了上述分析,总结了如何应用离焦星点图指导装调过程以及图像处理的方法。实验结果表明:无论是横向误差还是纵向误差,应用该方法得到的实验结果和理论分析值均符合得很好,其中通过倾斜调整彗差和偏心率调整像散误差均可控制在5%以内。

依据点云强度校正的壁画纠正

壁画纠正能消除数字壁画影像的变形并赋予其空间参数特性,是壁画数字化保护中的关键步骤之一。激光扫描数据作为壁画影像与三维空间的媒介,在壁画影像的纹理映射和纠正中具有重要的意义。然而,激光点云强度的近距离反常现象给壁画纠正中特征点的提取带来了困难。本文针对基于点云的壁画纠正中强度信息的近距离反常问题,研究了激光成像原理,推导了顾及激光接收系统散焦效应的强度函数,并采集样本数据进行模型参数估计,通过对估计模型和实际采集数据进行比较,生成不受距离和入射角影响的相对反射率,从而有效校正了强度异常的点云数据。试验表明,在壁画影像纠正过程中,该方法能有效解决强度影像提取特征点少且分布不均的问题,效果明显优于通用的数字图像处理方法。

星空环境成像效果的仿真研究

在分析星空环境下相机成像机理的基础上,从相机光学系统,光感受器工作特性和光圈衍射过程三个方面对星空环境下的成像系统进行了建模。基于这些模型,深入分析了星空环境下成像过程中背景离焦模糊,运动模糊和星芒这三种效果的形成原因并提出了针对性的模拟方法。应用这些方法的一系列仿真实验结果表明了所提方法的有效性。

对象引导的单幅散焦图像深度提取方法

2D图像转3D图像是解决3D影视内容缺乏的主要手段之一,而深度提取是其中的关键步骤.考虑到影视作品中存在大量散焦图像,提出单幅散焦图像深度估计的方法:首先通过高斯卷积将散焦图像转换成两幅模糊程度不同的图像;其次计算这两幅图像在边缘处的梯度幅值比例,进而根据阶跃信号与镜头的卷积模型得到边缘处的模糊度;再次将边缘处的模糊度转换成图像的稀疏深度并利用拉普拉斯矩阵插值得到稠密深度图;最后通过图像的视觉显著度提取前景对象,建立对象引导的深度图优化能量模型,使前景的深度趋于一致并平滑梯度较小区域的深度.该方法利用对象引导的深度优化,剔除了拉普拉斯矩阵插值引入深度图的纹理信息.模拟图像的峰值信噪比和真实图像的视觉对比均表明该算法比现有方法有较大改善.