透镜模型下基于色散和强度传输方程的相位恢复技术

针对基于强度传输方程（Transport of Intensity Equation, TIE）的非干涉相位恢复技术要求光源是单色的限制,以及强度采集过程移动CCD或物体而引入的机械误差,提出了一种适用于透镜模型下的色散相位恢复技术。该方法基于透镜成像系统的相位变换特性,将色散与TIE结合在一起, 使不同波长的光经过透镜系统后在同一位置成像,从而在不机械移动的情况下获得聚焦和散焦强度图像。再利用散焦量与波长的关系结合TIE计算出物体的相位信息。模拟实验中用该方法恢复物体的相位与原始相位的相关性系数为0.970 7,均方根误差为0.061 8;同时真实实验对透镜阵列相位进行了恢复,实验结果与真实参数误差为1.74%,证明了所提方法的正确性和有效性。     

一种多体制兼容的微波成像新技术

虚拟透镜成像技术是一种可以兼顾远、中、近不同距离的成像新技术,但该技术是在被动成像的基础 上发展起来的,适用于被动成像、半主动成像以及常规相控阵成像。在主动全息成像以及合成孔径成像系统中,由 于天线单元依次工作并收发信号,目标回波信号具有不同的传播路径和相位延迟特性,因而不能直接采用虚拟透镜 成像技术。文中对虚拟透镜成像技术进行扩展,针对主动全息成像和合成孔径成像的特点,引入了阵列属性参数, 将其与信号传播路径和相位延迟特性进行关联,建立了一种多体制兼容的成像快速算法统一架构,并对相位加权算 法进行了优化。所提出的新算法适用范围更广泛,且相位加权算法简洁易实现。最后进行了成像验证,实验及仿真 结果证实了新算法的有效性。     

一种基于共轴干涉的相位物体定量成像技术

为了实现生物组织及相位光栅等透明相位物体的快速定量相位测量与成像,基于共轴干涉及相衬干涉原理,构建了一套相位物体定量相位快速测量与成像系统。分析了定量成像原理,设计了相应的相位提取及恢复算法。通过拍摄单幅或两幅相衬图,实现了相位光栅、水滴等小相位变化的相位样品的定量相位测量与成像。设计了相应的分区差分相位解包裹算法,实现了相位值超过π的微透镜的定量相位测量与成像。结果表明,通过该系统测量所得到的全息相位光栅的相位分布以及不同超声驱动电压下弱超声驻波光栅的相位振幅变化关系与其它方法所得的测量结果基本一致;微透镜的实验测量厚度值与理论计算值相比,绝对误差约为0.03μm。本系统具有一定的可行性和适应性,在生物细胞和组织等透明相位物体的快速测量与成像方面有潜在的应用意义。     

强度传输方程和角谱迭代融合的相位检索算法

相位检索技术将光学与计算相结合,从强度测量中恢复相位,包括强度传输方程法和角谱迭代法。但前者仅对近场相位的恢复有效,其基于相干照明的假设前提使得该方法不能直接应用于自然场景的相位检索中;而后者具有迭代不确定性、收敛速度慢等缺点。探讨了在相干照明情况下传统强度传输方程法和角谱迭代法相融合的相位检索算法,将该融合法进一步扩展,提出了适用于自然场景透镜模型的相位检索方法,即使用强度传输方程法计算像平面的相位,并将该相位值作为角谱迭代的初始值,根据光路的可逆性,迭代出物面的相位信息,分别给出了两种情况下的实验结果。     

免偏振敏感消色差超构镜设计研究

超构透镜作为一种灵活调控空间光场相位、振幅及偏振的有效选择,在超分显微成像中受到了广泛的关注。为了提高多波长显微成像的分辨率,解决传统光学系统结构厚重、设计复杂等问题,基于相位补偿理论,运用传输相位法以及粒子群优化算法,设计了一种基于二氧化钛纳米单元柱的反射式消色差超构透镜,在500~550 nm之间实现了恒定聚焦,且该透镜具有偏振不敏感的特性。与数值孔径相同但有色散的超构透镜的对比结果有效证实了该超构透镜的消色差功能。所设计的透镜可应用于多波长显微成像系统中并提高成像的分辨率。此外,该消色差透镜在数码相机和光学仪器等领域中也有较好的应用价值。     

基于柱透镜多旋转测量的计算成像

提出一种基于单柱透镜旋转调制的光学扫描成像系统，样品的完整波前信息可以通过柱透镜旋转调制的多幅强度图样迭代重建。此外，柱透镜的旋转角度作为该系统的一个关键参数，其值通过基于Radon变换的数值计算方法得到，摆脱了对高精度旋转设备的要求。该成像系统的可行性在仿真和实验结果中均得以验证。与轴向多距离扫描成像系统相比，该成像系统中各光学元件在轴向位置保持固定，数据获取速度得以加快且轴向采样率保持固定，不仅简化了光场重构中的算法设计，而且极大地加快了收敛速度。     

一种基于数字外围约束的多距离相位恢复方法

相位恢复问题是物理光学领域的一个经典问题。基于迭代算法的传统多距离相位恢复方法利用多幅离焦强度实现波前重建，具有重建精度高、光学系统紧凑、稳定性高的特点。这类算法中的振幅与相位重建算法(Amplitude-Phase Retrieval, APR)能实现高质量复振幅重建，具有良好抗噪性能，但受限于其缓慢的收敛速度和停滞问题，导致成像对比度低。提出在迭代过程中灵活获取样本数字外围，将支撑域约束与APR算法结合，以改进标准APR算法的收敛速度和收敛精度，数值仿真验证了该算法的有效性，具有可移植性和实际应用价值。     

相位恢复算法研究进展

相位恢复技术是波前重构技术的一个重要分支,重构的结果只取决于测量平面光强的分布,相比于其他的波前重构方法,相位恢复技术具有不需要在光路中添加额外硬件、光路简单、对光路环境的要求低、抗干扰能力强等优点,在光束整形、激光光束净化和干涉成像等领域有着非常广阔的应用前景。相位恢复的精度及速度是评价相位恢复技术的主要准则,此领域目前文献比较繁杂,本文梳理了相位恢复算法的发展脉络,围绕相位恢复算法的收敛精度与收敛速度等核心问题,系统的介绍了迭代及光强相位恢复算法的相关研究进展,并且对相位恢复算法的发展前景进行了展望。     

单透镜系统中与色散融合的混合相位恢复方法

相位恢复是利用能观测到的强度信息恢复原始相位信息。强度传输方程（TIE）作为一种传统的非干涉相位恢复技术,只需通过测量至少两个相近平面的强度信息即可计算出相位信息。这种方法通常需要通过移动被测物体或摄像机来获取强度图像,不可避免地会产生机械误差。提出了一种新的相位恢复方法:与色散融合的混合相位恢复算法（CD-HPR）。通过设置不同波长的光通过单透镜系统得到物体在同一位置成的像,这样不需要机械运动就能获得聚焦和散焦图像强度,然后结合散焦量与波长之间的关系计算出散焦量,再用强度传输方程计算初始相位信息。角谱迭代算法的使用较好地改进了初始相位值。在仿真实验中,该方法恢复的相位与原始相位之间的均方差为0.1076;同时,通过实验恢复了透镜阵列的相位,实验结果与实际参数的误差为3.4%,证明了该方法的正确性和有效性。该方法扩展了传统方法要求光源为单色的局限性,提高了计算精度。     

激光反射层析成像相位恢复算法研究

针对激光反射层析成像中目标随机抖动与径向运动造成的投影中心失配问题,提出采用相位恢复算法对重构图像进行相位恢复重建,通过反复光强迭代消除目标随机运动造成的相位误差,达到减少重构误差、恢复目标图像的目的。为改进G-S算法收敛速度与恢复精度,提出频域模值加权方法进行投影数据相位迭代恢复,仿真实验表明,将算法收敛速度与收敛精度提高了1.2倍以上。通过对三组仿真实验处理,重构图像的平均相对均方误差由2.487 5下降到0.792 7,有效地恢复了目标图像轮廓。外场实验表明,该算法能够有效消除重构图像伪迹,改善激光反射层析成像系统成像质量。     

An improved method for MRI artifact correction due to translational motion in the imaging plane

A computer postprocessing technique is developed to remove MRI artifact arising from unknown translational motion in the imaging plane. Based on previous artifact correction methods, the improved technique uses two successive steps to reduce read out and phase-encoding direction artifacts: First, the spectrum shift method is applied to remove read-out axis translational motion. Then, the phase retrieval method is employed to eliminate the remaining subpixel motion of the read-out axis and the entire motion of the phase-encoding axis. In the presence of noise, to protect edge detection (in the spectrum shift method), two high-density gray-level markers are added, one to each side of the imaging object. Experimental results with an actual MR scan confirmed the ability of the method to correct the artifact of an MR image caused by unknown translational motion in the imaging plane     

MRI artifact cancellation due to rigid motion in the imaging plane

A post-processing technique has been developed to suppress the magnetic resonance imaging (MRI) artifact arising from object planar rigid motion. In two-dimensional Fourier transform (2-DFT) MRI, rotational and translational motions of the target during magnetic resonance magnetic resonance (MR) scan respectively impose nonuniform sampling and a phase error an the collected MRI signal. The artifact correction method introduced considers the following three conditions: (1) for planar rigid motion with known parameters, a reconstruction algorithm based on bilinear interpolation and the super-position method is employed to remove the MRI artifact, (2) for planar rigid motion with known rotation angle and unknown translational motion (including an unknown rotation center), first, a super-position bilinear interpolation algorithm is used to eliminate artifact due to rotation about the center of the imaging plane, following which a phase correction algorithm is applied to reduce the remaining phase error of the MRI signal, and (3) to estimate unknown parameters of a rigid motion, a minimum energy method is proposed which utilizes the fact that planar rigid motion increases the measured energy of an ideal MR image outside the boundary of the imaging object; by using this property all unknown parameters of a typical rigid motion are accurately estimated in the presence of noise. To confirm the feasibility of employing the proposed method in a clinical setting, the technique was used to reduce unknown rigid motion artifact arising from the head movements of two volunteers.     

Reconstruction of Double-Exposed Terahertz Hologram of Non-isolated Object

When the non-isolated imaging objects are complex or critical imaging precision is required, single-exposure digital hologram technique may be insufficient. So in this paper, double-exposure method is adopted in 2.52-THz inline digital holography simulations and experiments. Experimental results indicate that, compared with the results reconstructed by single-exposure amplitude-constrained phase retrieval algorithm (S-APRA), double-exposure phase-constrained phase retrieval algorithm (D-PPRA) increases the contrast of the reconstruction image by 0.146 and double-exposure amplitude-constrained phase retrieval algorithm (D-APRA) increases the contrast by 0.225. In addition, when applied to non-isolated object reconstruction, phase retrieval algorithms with only amplitude constraint on the object plane work better than those with both amplitude and phase constraints.     

Weighted haze removal method with halo prevention

In this paper, we propose an efficient method to remove haze from a signal image based on the atmospheric scattering model and dark channel prior. Our approach applies a weighted technique that automatically finds the possible atmospheric lights, and mixes these candidates to refine the atmospheric light. Then, difference prior, a novel prior processing method, is employed for the estimation of the transmission that mitigates the halo artifact around the sharp edges. This method requires a low computational cost and is suitable for real-time applications. The experimental results show that our approach obtains the comparable results as compared with previous methods.     

高通量快速傅里叶叠层显微成像技术研究进展

傅里叶叠层显微术（Fourier ptychographic microscopy,FPM）是一极具前景的计算成像技术,它具有高分辨率、大视场、无标记和定量相位等优势。由于它灵活的系统、高对比度的成像结果、无需干涉装置和光源机械扫描部件,在数字病理学、体外细胞无标记观察和实时监测等方面得到了大量的研究和应用。文中主要介绍了FPM技术的系统误差校正方法、基于FPM的高通量显微成像和高速显微成像技术研究的基本原理、研究现状和最新进展,提出了目前面临的问题以及未来的发展趋势。     

94-GHz Imager With Extended Depth of Field

We describe a computational imaging technique to extend the depth-of-field of a 94-GHz imaging system. The technique uses a cubic phase element in the pupil plane of the system to render system operation relatively insensitive to object distance. However, the cubic phase element also introduces aberrations but, since these are fixed and known, we remove them using post-detection signal processing. We present experimental results that validate system performance and indicate a greater than four-fold increase in depth-of-field from 17” to greater than 68”.      

基于改进MNE算法的动目标检测技术

在多通道SAR/GMTI系统中,对各通道回波数据分别成像后采用最小范数特征相消法(MNE)进行二维自适应处理,可以有效地宾现杂波和干扰的抑制,提高动目标检测性能,但算法运算量较大,不利于实时处理.首先对MNE基本原理进行分析,在此基础上,将近似投影子空间跟踪(PAST)技术引入到MNE中,提出了一种基于PAST的MNE算法用于多通道SAR动目标检测.与常规的MNE算法相比,新算法抑制杂波性能相当,但运算量有所降低,最后利用实测数据验证了该算法的有效性和优越性.     

Accelerating near-field 3D imaging approach for joint high-resolution imaging and phase error correction

The computational complexity and memory requirements of large-scale data seriously affect the application of compressed sensing (CS) in near-field three-dimensional (3-D) imaging system. In addition, as influenced by the measurement environment, the error in echo phase results in imaging defocusing. This paper proposes a CS near-field 3-D imaging approach based on nonuniform fast Fourier transform and phase error correction. It applies the fast Gaussian gridding nonuniform fast Fourier transform technique and Separable Surrogate Functionals with only matrix and vector multiplied to accelerate imaging speed and reduce memory requirements; it adopts the phase error correction technique to realize highly-focused imaging; in addition, a sparse observation approach based on Logistic sequence is proposed in this paper for easy availability of engineering realization for CS imaging. As indicated by numerical analysis and actual measurement in anechoic chamber, the approach proposed in this paper, compared with traditional imaging approaches, has the following advantages: accurate high resolution 3-D image of target can be obtained by applying small amount of observation data (10%); the computational complexity falls from O(LN) to O(3N) and memory occupation quantity drops from O(LN) to O(N); it can effectively perform highly-focused imaging for echo signal with phase error; the measurement matrix designed has better non-coherence and easy availability for engineering realization.

     

Signal decomposition of transmembrane voltage-sensitive dye fluorescence using a multiresolution wavelet analysis

Fluorescence imaging of transmembrane voltage-sensitive dyes is used to study electrical activation in cardiac tissue. However, the fluorescence signals, typically, have low SNRs and may be contaminated with motion artifact. In this report, we introduce a new processing approach for fluoresced transmembrane potentials (fTmps) that is based upon a discrete wavelet transform. We show how fTmp signals can be decomposed and reconstructed to form three subsignals that contain signal noise (noise signal), the early depolarization phase of the action potential (rTmp signal), and motion artifact (rMA signal). A coiflet4 wavelet is used for fTmp decomposition and reconstruction of these subsignals. Results using fTmp signals that are contaminated with motion artifact indicate that the approach is a useful processing step to remove baseline drift, reduce noise, and reveal wavefronts. It streamlines the preprocessing of fTmps for the subsequent measurement of activation times and conduction velocities. It is a promising approach for studying wavefronts without aggressive mechanical tissue constraint or electromechanical uncoupling agents and is, useful for single-camera systems that do not provide for ratiometric imaging.     

On the efficient evaluation of probabilistic similarity functions for image retrieval

Probabilistic approaches are a promising solution to the image retrieval problem that, when compared to standard retrieval methods, can lead to a significant gain in retrieval accuracy. However, this occurs at the cost of a significant increase in computational complexity. In fact, closed-form solutions for probabilistic retrieval are currently available only for simple probabilistic models such as the Gaussian or the histogram. We analyze the case of mixture densities and exploit the asymptotic equivalence between likelihood and Kullback-Leibler (KL) divergence to derive solutions for these models. In particular, 1) we show that the divergence can be computed exactly for vector quantizers (VQs) and 2) has an approximate solution for Gauss mixtures (GMs) that, in high-dimensional feature spaces, introduces no significant degradation of the resulting similarity judgments. In both cases, the new solutions have closed-form and computational complexity equivalent to that of standard retrieval approaches.