Restoration of atmospheric turbulence degraded images

A blind image deconvolution algorithm in the frequency domain is proposed which uses the edge-preserving method and generic bandwidth of optical system. Generic bandwidth of optical system is analyzed. With the benefits of bandwidth and edge-preserving method as compelling constraints, the algorithm cannot only suppress noise effectively but also restrict the bandwidth of point-spread function (PSF), so high-quality result can be obtained. The new algorithm is superior in handling unregistered channels. The performance of this approach is investigated with simulated data. As shown in our investigation, the algorithm can significantly alleviate the artifacts produced by the deconvolution process.     

Total variation based gradient descent algorithm for sparse-view photoacoustic image reconstruction

In photoacoustic imaging (PAI), reconstruction from sparse-view sampling data is a remaining challenge in the cases of fast or real-time imaging. In this paper, we present our study on a total variation based gradient descent (TV-GD) algorithm for sparse-view PAI reconstruction. This algorithm involves the total variation (TV) method in compressed sensing (CS) theory. The objective function of the algorithm is modified by adding the TV value of the reconstructed image. With this modification, the reconstructed image could be closer to the real optical energy distribution map. Additionally in the proposed algorithm, the photoacoustic data is processed and the image is updated individually at each detection point. In this way, the calculation with large matrix can be avoided and a more frequent image update can be obtained. Through the numerical simulations, the proposed algorithm is verified and compared with other reconstruction algorithms which have been widely used in PAI. The peak signal-to-noise ratio (PSNR) of the image reconstructed by this algorithm is higher than those by the other algorithms. Additionally, the convergence of the algorithm, the robustness to noise and the tunable parameter are further discussed. The TV-based algorithm is also implemented in the in vitro experiment. The better performance of the proposed method is revealed in the experiments results. From the results, it is seen that the TV-GD algorithm may be a practical and efficient algorithm for sparse-view PAI reconstruction.     

结合基于梯度的振铃评价算法的总变分最小化图像分块复原法

为了消除退化函数随空间变化发生变化模糊图像分块复原法子块之间的不平滑拼接缝,提出了一种结合了基于梯度的振铃评价算法梯度振铃评价(GRM)的总变分(TV)最小化分块复原法.根据图像分布及退化类型将模糊图像划分为矩形、环形或其他形状的子块,图像子块之间要留有一定的重叠区;然后对每一个图像子块进行复原,GRM方法是基于图像梯度结构相似度的图像质量评价算法,以GRM作为TV复原算法迭代过程中的收敛条件,可以更好地控制复原图像的振铃;最后去除复原图像子块含振铃波纹的重叠区,拼接得到完整图像.并以矩形分块及环形分块为例,证明该方法可以很好地抑制图像边界振铃效应,克服分块复原法本身的缺陷,得到拼接平滑的完整图像.     

基于全变差的弱小目标背景抑制

结构化背景抑制是红外弱小目标检测技术的一个难题。根据红外图像中目标和背景信号的特性,在定义Gabor函数为点扩展函数的基础上,提出了一种基于全变差滤波的背景抑制算法,该算法将图像的背景抑制转化为求解全变差滤波模型最小化,以便最终实现对红外图像的背景抑制。对真实的红外图像序列进行实验,并与小波域滤波算法进行了比较。几组实验结果表明,对在结构化背景下的红外弱小目标背景来说,从主观视觉和数值指标来看,该算法具有良好的抑制效果,且运算量较小,便于实时实现。     

Estimating missing information by maximum likelihood deconvolution

The ability of iteratively constrained maximum likelihood (ML) deconvolution to reconstruct out-of-band information is discussed and exemplified by simulations. The frequency dependent relative energy regain, a novel way of quantifying the reconstruction ability, is introduced. The positivity constraint of ML deconvolution allows reconstructing information outside the spatial frequency bandwidth which is set by the optical system. This is demonstrated for noise-free and noisy data. It is also shown that this property depends on the type of object under investigation. An object is constructed where no significant out-of-band reconstruction is possible. It is concluded that in practical situations the amount of possible out-of-band reconstruction depends on the agreement between reality and the model describing "typical objects" incorporated into the algorithm by appropriate penalty functions.     

基于全变分正则化的高能闪光照相消模糊图像重建算法

 针对高能闪光照相投影图像消模糊难度大的问题,提出了一种基于全变分正则化的消模糊图像重建算法,该算法根据闪光照相的成像特点,将客体的纵向截面作为一个整体来进行建模,并在重建方程中考虑了模糊因素,然后采用全变分范数作为正则项,构建了用于消模糊图像重建的展平泛函,将消模糊图像重建问题转化为能量泛函极小化问题,通过固定点迭代算法求解图像重建问题的最小化解。数值模拟结果表明：该算法由于考虑了闪光照相成像时的图像模糊因素,在重建时能够较好地消除模糊对重建结果的影响,在抑制噪声的同时能较好地保持图像的边缘信息,有利于提高重建图像的质量。     

Imaging and quantifying transverse flow velocity with the Doppler bandwidth in a phase-resolved functional optical coherence tomography

The Doppler bandwidth extracted from the standard deviation of the frequency shift in phase-resolved functional optical coherence tomography (F-OCT) was used to image the velocity component that is transverse to the optical probing beam. It was found that above a certain threshold level the Doppler bandwidth is a linear function of flow velocity and that the effective numerical aperture of the optical objective in the sample arm determines the slope of this dependence. The Doppler bandwidth permits accurate measurement of flow velocity without the need for precise determination of flow direction when the Doppler flow angle is within +/-15 degrees perpendicular to the probing beam. Such an approach extends the dynamic range of flow velocity measurements obtained with the phase-resolved F-OCT.     

微弱光学图像的光参量放大特性的研究

研究了微弱光学图像在光参量图像放大中的放大特性,分析了相位匹配和晶体的空间频率带宽对图像信号增益的影响,从实验上验证了不同的相位匹配时输入图像信号在傅里叶平面上的增益分布.结果表明,当晶体的空间频率带宽大于输入图像信号的空间频率带宽且完全相位匹配时,光参量图像放大器能够对输入图像信号实现无失真、高增益的理想放大;有相位失配时,图像信号的增益峰值向高空间频率范围移动,并且在峰值附近范围变窄,随相位失配量大小的变化能够对图像信号光场中某特定空间频率实现放大,对图像信号进行滤波处理,突出图像特定频率的信息,实现图像边缘增强.     

总变差约束的数据分离最小图像重建模型及其Chambolle-Pock求解算法

基于优化的迭代法,可以结合压缩感知和低秩矩阵等稀疏优化技术高精度地重建图像.其中,总变差最小（total variation minimization,TV）模型是一种简单有效的优化模型.传统的约束TV模型,使用数据保真项为约束项,TV正则项为目标函数.本文研究TV约束的、数据分离最小（TV constrained,data divergence minimization,TVcDM）新型TV模型及其求解算法.详细推导了TVcDM模型的Chambolle-Pock（CP）算法,验证了模型及算法的正确性;分析了算法的收敛行为;评估了模型的稀疏重建能力;分析了模型参数的选择对重建的影响及算法参数对收敛速率的影响.研究表明,TVcDM模型有高精度稀疏重建能力;TVcDM-CP算法确保收敛,但迭代过程中有振荡现象;TV限对重建有重要影响,参数值过大会引入噪声而过小会模糊图像细节;算法参数的不同选取会导致不同的收敛速率.     

双树复数小波变换的视网膜图像半盲解卷积复原

针对导致自适应光学视网膜图像降质退化的原因,提出了一种结合双树复数小波变换(DTCWT)和图像半盲解卷积复原算法的方法。首先,对经过自适应光学实时校正技术得到的视网膜图像进行DT-CWT分解,得到低频和高频部分应的图像。将自适应光学成像系统中残余像差重建的光学传递函数作为图像复原模型的初始估计点扩散函数(PSF),并对低频部分图像进行条件约束的迭代半盲解卷积复原;对高频部分的图像进行去噪处理。最后,将处理后的高频和低频部分图像进行双树复数小波逆变换,获得复原图像。实验和结果表明:由该方法处理的视网膜细胞图像质量得到明显提高,图像客观质量评价参数相对于原始图像提高了5倍多;在视网膜细胞的空间频率范围内(70~90(°)~1),复原图像功率谱平均值提高了5倍左右,有助于对视网膜细胞的高分辨率观察。     

Cyclic polling-based dynamic wavelength and bandwidth allocation in wavelength division multiplexing passive optical networks

Cyclic polling-based dynamic wavelength and bandwidth allocation algorithm supporting differentiated classes of services in wavelength division multiplexing （WDM） passive optical networks （PONs） is proposed. In this algorithm, the optical line terminal （OLT） polls for optical network unit （ONU） requests to transmit data in a cyclic manner. Services are categorized into three classes： expedited forward （EF） priority, assured forwarding （AF） priority, and best effort （BE） priority. The OLT assigns bandwidth for different priorities with different strategies. Simulation results show that the proposed algorithm saves a lot of downstream bandwidth under low load and does not show the light-load penalty compared with the simultaneous and interleaved polling schemes.     

A new family of two-dimensional triple-codeweight asymmetric optical orthogonal code for OCDMA networks

A new generation algorithm of two-dimensional triple-codeweight asymmetric optical orthogonal codes for optical code division multiple access （OCDMA） networks is proposed. The code cardinality is obtained and the error-probability performance for corresponding OCDMA system is analyzed. The codes with two constraints （i.e., auto- and cross-correlation properties） being unequal are taken into account. On the premise of fixed system resources, the code of the error-probability performance, it is shown cardinality can be significantly improved. By analysis that the codes with different parameters have different performances. Therefore, this type of codes can be applied to support diverse quality of service （QoS） and satisfy the quality requirement of different multimedia or distinct users, and simultaneously make the better use of bandwidth resources in oDtical networks.     

邻域差值法确定灰度变换的分段点

光电跟踪测量设备电视系统受到自然条件的影响,往往捕获不到清晰的画面,很容易出现对比度极低的图像。针对此种情况,提出了一种用邻域差值来确定分段点的灰度变换法。通过计算像素55邻域的灰度差值,取最小的12个值之和ND。在大量实验的基础上确定合适的阈值T,与ND相比较,确定出图像边缘像素的灰度值范围,据此确定分段灰度变换公式的分段点。实验结果表明,在原图像对比度为1.19%的基础上,通过该算法处理后图像的对比度是原图像的18.79倍,是直方图均衡化后图像的6.97倍,是直方图规定化后图像的41.41倍,图像对比度达到了22.36%,图像的直方图也由单峰突出变为比较均衡的状态。该算法无论在数据上还是在视觉上都取得了很好的效果,满足了电视系统的跟踪要求,已经应用在光电跟踪测量设备上,有较好的实用价值。     

Analyzing wavelength behavior of a cubic phase mask imaging system based on modulation transfer function

The wavefront coding technology is an effectively method for extending the depth of field. However, the phase delayed by the phase mask changes with light wavelength, and the chromatic aberration is caused by chromatic dispersion of the optical elements. The modulation transfer function (MTF) of the cubic phase mask (CPM) system is derived with considering the axial chromatic aberration and optical path difference variation with wavelength, and the wavelength behavior of CPM system is analyzed in details. We yield that the MTF is approximately wavelength invariant within a certain frequency bandwidth, and the bandwidth is nearly inverse proportional to wavelength and varies with axial chromatic aberration. The effect induced by dispersion of the CPM material is very weak. If the CPM system is illuminated by wideband spectral light and the ACA exists, then the frequency bandwidth may become narrower than the monochromatic case, and the position of image sensor can be relocated to balance frequency bandwidth among all wavelengths.     

一种在光网络实现流量工程的快捷的路由算法

提出了一种在光网络中实现流量工程的快捷的有带宽保证的负载均衡动态路由算法。该算法通过提出期望负载率的概念和新定义的链路关键度函数以及链路当前可用带宽确定链路动态成本，并依据该动态成本运用最短路径优先算法为到达的LSP请求建立动态成本优化路径。仿真实验表明，与其他算法相比，该算法在降低LSP建立请求服务拒绝率、均衡网络负载以及链路失效后重路由等方面有更好的性能。     

An Efficient Proximity Point Algorithm for Total-Variation-Based Image Restoration

In this paper, we propose a fast proximity point algorithm and apply it to total variation (TV) based image restoration. The novel method is derived from the idea of establishing a general proximity point operator framework based on which new first-order schemes for total variation (TV) based image restoration have been proposed. Many current algorithms for TV-based image restoration, such as Chambolle's projection algorithm, the split Bregman algorithm, the Bermúdez-Moreno algorithm, the Jia-Zhao denoising algorithm, and the fixed point algorithm, can be viewed as special cases of the new first-order schemes. Moreover, the convergence of the new algorithm has been analyzed at length. Finally, we make comparisons with the split Bregman algorithm which is one of the best algorithms for solving TV-based image restoration at present. Numerical experiments illustrate the efficiency of the proposed algorithms.     

基于正交频分复用无源光网络的动态带宽分配算法研究

介绍了一种应用于未来大容量、多业务接入场景下的称为光正交频分复用无源光网络的下一代接入网技术,并提出了一种基于此结构的称为基于服务质量需求的固定周期流水线轮询动态带宽分配算法.该算法通过应用二级带宽分配机制、带宽预申请机制和最小带宽申请优先原则等方法,有效地保障了在大容量、多业务接入场景下各个业务不同的服务质量需求.为...     

空间变化PSF非盲去卷积图像复原法综述

传统的图像复原一般认为点扩散函数(PSF)是空间不变的,实际光学系统由于受到像差等因素的影响,并非严格的线性空间不变系统,基于空间变化PSF的非盲去卷积图像复原法逐渐体现其优越性。空间变化PSF的非盲去卷积图像复原法先准确估计图像空间变化的PSF,再利用非盲去卷积算法对图像进行复原,有利于恢复出高质量图像。本文从算法的角度综述了近几年提出的基于空间变化PSF的非盲去卷积图像复原方法,并对比了基于强边缘预测估计PSF的非盲去卷积法、基于模糊噪声图像对PSF估计非盲去卷积法等算法的优缺点,各算法分别在PSF估计精确度、振铃效应抑制效果、适用范围等方面体现出各自的优劣。空间变化PSF的非盲去卷积图像复原法的研究,有利于推进图像复原技术向更高水平发展,使光学系统往轻小型化方向发展,从而在多个科学领域发挥其重要作用。     

基于随机点扩散函数的多帧湍流退化图像自适应复原方法

针对湍流退化图像随机性的问题,提出了一种基于随机点扩散函数的多帧湍流退化图像自适应复原方法。首先介绍了随机点扩散函数的图像退化模型,并分析了点扩散函数随机性对图像复原造成的影响,建立了基于随机点扩散函数的多帧图像退化模型。在此基础上,建立了基于多帧退化图像的全变分复原模型,利用前向后向算子分裂法对模型进行求解,提高了算法的运算效率。然后,提出了一种新的自适应正则化参数选取方法,该方法利用全变分复原模型的目标函数计算正则化参数,当正则化参数收敛时,复原图像的峰值信噪比达到最大值,因此利用目标函数的相对差值作为自适应算法迭代终止的条件,可以获得最佳复原效果。最后通过实验分析,算法中退化图像的帧数应不大于10帧。实验结果表明:当取10帧退化图像时,AFBS算法运算时间与单帧的FBS算法相当,信噪比增益为1.4 dB。本文算法对图像噪声有明显的抑制作用,对湍流退化图像可以获得较好的复原效果。     

Reconstruction of dynamic contrast enhanced magnetic resonance imaging of the breast with temporal constraints

A number of methods using temporal and spatial constraints have been proposed for reconstruction of undersampled dynamic magnetic resonance imaging (MRI) data. The complex data can be constrained or regularized in a number of different ways, for example, the time derivative of the magnitude and phase image voxels can be constrained separately or jointly. Intuitively, the performance of different regularizations will depend on both the data and the chosen temporal constraints. Here, a complex temporal total variation (TV) constraint was compared to the use of separate real and imaginary constraints, and to a magnitude constraint alone. Projection onto Convex Sets (POCS) with a gradient descent method was used to implement the diverse temporal constraints in reconstructions of DCE MRI data. For breast DCE data, serial POCS with separate real and imaginary TV constraints was found to give relatively poor results while serial/parallel POCS with a complex temporal TV constraint and serial POCS with a magnitude-only temporal TV constraint performed well with an acceleration factor as large as R=6. In the tumor area, the best method was found to be parallel POCS with complex temporal TV constraint. This method resulted in estimates for the pharmacokinetic parameters that were linearly correlated to those estimated from the fully-sampled data, with K^trans,R=6=0.97 K^trans,R=1+0.00 with correlation coefficient r=0.98, k_ep,R=6=0.95 k_ep,R=1+0.00 (r=0.85). These results suggest that it is possible to acquire highly undersampled breast DCE-MRI data with improved spatial and/or temporal resolution with minimal loss of image quality.