Iterative reconstruction method in phase-diversity imaging

An object is iteratively reconstructed from two atmospherically degraded images, one of which is detected by shifting of a known amount of phase with respect to the other. The iterative reconstruction scheme is based on the ideas of the blind-deconvolution method and the error-reduction algorithm. An optical system to do phase shifting is proposed in which a deformable mirror is employed. Several computer simulations are conducted to exemplify the usefulness of our method.     

Evaluation of least-squares phase-diversity technique for space telescope wave-front sensing

Because of mechanical aspects of fabrication, launch, and operational environment, space telescope optics can suffer from unforeseen aberrations, detracting from their intended diffraction-limited performance goals. We give the results of simulation studies designed to explore how wave-front aberration information for such near-diffraction-limited telescopes can be estimated through a regularized, low-pass filtered version of the Gonsalves (least-squares) phase-diversity technique. We numerically simulate models of both monolithic and segmented space telescope mirrors; the segmented case is a simplified model of the proposed next generation space telescope. The simulation results quantify the accuracy of phase diversity as a wave-front sensing (WFS) technique in estimating the pupil phase map. The pupil phase is estimated from pairs of conventional and out-of-focus photon-limited point-source images. Image photon statistics are simulated for three different average light levels. Simulation results give an indication of the minimum light level required for reliable estimation of a large number of aberration parameters under the least-squares paradigm. For weak aberrations that average a 0.10lambda pupil rms, the average WFS estimation errors obtained here range from a worst case of 0.057lambda pupil rms to a best case of only 0.002lambda pupil rms, depending on the light level as well as on the types and degrees of freedom of the aberrations present.     

Multiframe superresolution of binary images

We describe a new algorithm for superresolving a binary object from multiple undersampled low-resolution (LR) images that are degraded by diffraction-limited optical blur, detector blur, and additive white Gaussian noise. Two-dimensional distributed data detection (2D4) is an iterative algorithm that employs a message-passing technique for estimating the object pixel likelihoods. We present a novel non-training-based complexity-reduction technique that makes the algorithm suitable even for channels with support size as large as 5 x 5 object pixels. We compare the performance and computational complexity of 2D4 with that of iterative backprojection (IBP). In an imaging system with an optical blur spot matched to the object pixel size, 2 x 2 undersampled measurement pixels, and four LR images, the reconstruction error measured in terms of the number of pixel mismatches for 2D4 is 300 times smaller than that for IBP at a signal-to-noise ratio of 38 dB.     

Multiframe image estimation for coded aperture snapshot spectral imagers

A coded aperture snapshot spectral imager (CASSI) estimates the three-dimensional spatiospectral data cube from a snapshot two-dimensional coded projection, assuming that the scene is spatially and spectrally sparse. For less spectrally sparse scenes, we show that the use of multiple nondegenerate snapshots can make data cube recovery less ill-posed, yielding improved spatial and spectral reconstruction fidelity. Additionally, data acquisition can be easily scaled to meet the time/resolution requirements of the scene with little modification or extension of the original CASSI hardware. A multiframe reconstruction of a 640 × 480 × 53 voxel datacube with 450-650 nm white-light illumination of a scene reveals substantial improvement in the reconstruction fidelity, with limited increase in acquisition and reconstruction time.     

Angle density functions for active sensor imaging

A new target density function (TDF) is proposed for active sensor imaging. The TDF, called the angle density function, is studied by utilising the angular distribution of targets at a fixed range. Active sensor imaging based on the angle density function is achieved using a phased array radar system. The phased array system is arranged for stationary radar-stationary target configuration. The imaging algorithm is applied for the whole target area. Instead of pointwise imaging, an approach including the whole target area globally is developed. An advantage of the technique is the use of standard Fourier-based analysis. This makes it possible to use of simple functions for global radar imaging. Although the imaging is accomplished by way of the phased array radars, beamforming is not necessary with the proposed technique.     

结构主动控制最优极点配置算法研究

针对结构主动控制极点配置理论所得控制力矩阵的不唯一性,提出一种基于结构主动控制极点配置的优化算法。该算法与经典LQR最优主动控制主要区别表现在用于结构主动控制时不受加权矩阵Q和R的影响,具有明显的物理或工程意义。首先,对比了结构主动控制系统各数学模型之间的相互关系,依据传递函数矩阵的唯一性, 在复平面内进行最优零极点配置;其次,构造基于期望零极点的目标传递函数矩阵,并对传递函数矩阵进行目标最小实现,从而实现结构主动控制的最优极点配置;最后采用算例说明本文算法的有效性和实用性。     

Cramer-Rao bound and phase-diversity blind deconvolution performance versus diversity polynomials

Information theoretic bounds on the estimated Zernike coefficients for various diversity phase functions are presented. We show that, in certain cases, defocus diversity may yield a higher Cramer-Rao lower bound (CRLB) than some other diversity phase functions. Using simulated images to evaluate the performance of the phase-diversity algorithm, we find that, for an extended scene and defocus diversity, the phase-diversity algorithm achieves the CRLB for known objects. Furthermore, the phase-diversity algorithm achieves the CRLB by a factor of approximately 2 for unknown objects.     

一种灰度成像扩展目标跟踪方法

灰度图像色彩信息贫乏会导致易陷于局部相似,使跟踪点发生漂移。针对此问题,提出了基于目标成像空间域与特征域分布的改进直方图模式扩展目标跟踪算法。以基于像素位置和像素灰度值的直方图模式作为目标模式;相似度测量采用基于Bhattacharyya系数定义的距离;用均值偏移迭代进行匹配区域搜索;通过建立卡尔曼预测跟踪策略解决目标被遮挡时的跟踪问题。试验结果表明,采用该算法,跟踪点漂移由原来十几个像素的波动减少到仅偶有1个像素的抖动。     

Multiframe image super-resolution adapted with local spatial information

Super-resolution image reconstruction, which has been a hot research topic in recent years, is a process to reconstruct high-resolution images from shifted, low-resolution, degraded observations. Among the available reconstruction frameworks, the maximum a posteriori (MAP) model is widely used. However, existing methods usually employ a fixed prior item and regularization parameter for the entire HR image, ignoring local spatially adaptive properties, and the large computation load caused by the solution of the large-scale ill-posed problem is another issue to be noted. In this paper, a block-based local spatially adaptive reconstruction algorithm is proposed. To reduce the large computation load and realize the local spatially adaptive process of the prior model and regularization parameter, first the target image is divided into several same-sized blocks and the structure tensor is used to analyze the local spatial properties of each block. Different property prior items and regularization parameters are then applied adaptively to different properties' blocks. Experimental results show that the proposed method achieves better performance than methods with a fixed prior item and regularization parameter.     

Multiframe blind deconvolution of heavily blurred astronomical images

A multichannel blind deconvolution algorithm that incorporates the maximum-likelihood image restoration by several estimates of the differently blurred point-spread function (PSF) into the Ayers-Dainty iterative algorithm is proposed. The algorithm uses no restrictions on the image and the PSFs except for the assumption that they are positive. The algorithm employs no cost functions, input parameters, a priori probability distributions, or the analytically specified transfer functions. The iterative algorithm permits its application in the presence of different kinds of distortion. The work presents results of digital modeling and the results of processing real telescope data from several satellites. The proof of convergence of the algorithm to the positive estimates of object and the PSFs is given. The convergence of the Ayers-Dainty algorithm with a single processed frame is not obvious in the general case; therefore it is useful to have confidence in its convergence in a multiframe case. The dependence of convergence on the number of processed frames is discussed. Formulas for evaluating the quality of the algorithm performance on each iteration and the rule of stopping its work in accordance with this quality are proposed. A method of building the monotonically converging subsequence of the image estimates of all the images obtained in the iterative process is also proposed.     

卫星主动控温回路的设计模型与算法

使用电加热器的卫星主动控温回路是一种重要的主动热控措施,通过简明扼要的机理分析建立起该主动控温过程中受控对象温度变化的动态方程,得出了稳态控温、瞬态控温两种基本的控温模式下主动控温回路电加热器功率需求的计算表达式,给出了进行主动控温回路电加热器热功率设计计算的一般流程,较详细地分析了一个具体设计算例,为卫星主动控温回路设计计算提供了简便的计算模型和方法。     

Comparison of speckle reduction diversity tools for active millimeter-wave imaging

Imaging concealed objects with millimeter-wave coherent radiation is accompanied by speckle. Like all interference phenomena, speckle depends on three light parameters of the millimeter-wave laser beam--phase, wavelength, and angle of incidence--and can be reduced by the diversity of these three parameters. Diversity tools to improve images of concealed objects have been compared. We report measurements, simulations, and image reconstruction results over the whole W-band (75-110 GHz) and demonstrate where each tool works the best. Multiphase diversity is successful in reducing speckle contrast: multiangle to improve the image quality, and multispectral to recognize a small object's features. A simple postprocessing eliminates the areas still covered by interference.     

Comparison of passive ranging integral imaging and active imaging digital holography for three-dimensional object recognition

We present an overview of three-dimensional (3D) object recognition techniques that use active sensing by interferometric imaging (digital holography) and passive sensing by integral imaging. We describe how each technique can be used to retrieve the depth information of a 3D scene and how this information can then be used for 3D object recognition. We explore various algorithms for 3D recognition such as nonlinear correlation and target distortion tolerance. We also provide a comparison of the advantages and disadvantages of the two techniques.     

汽车车内噪声主动控制变步长NFB-LMS算法

为规避最小均方（Least Mean Square,LMS）算法不能同时提高收敛速度和降低稳态误差的固有缺陷,以及已有变步长LMS算法存在收敛速度慢和稳态误差估计精度差的问题,文中提出了一种基于变步长归一化频域块（Normalized Frequency-domain Block,NFB） LMS算法的汽车车内噪声主动控制方法。为了比较,应用传统的LMS算法、基于反正切函数的变步长LMS算法和变步长NFB-LMS算法分别进行实测汽车车内噪声的主动控制。结果表明,与其他两个算法相比,变步长NFB-LMS算法的收敛速度提高了70%以上,稳态误差减小了90%以上。变步长NFB-LMS算法在处理车内噪声信号时具有很高的效率,为进行汽车车内噪声主动控制提供了一种新方法。     

The wavenumber algorithm for full-matrix imaging using an ultrasonic array

Ultrasonic imaging using full-matrix capture, e.g., via the total focusing method (TFM), has been shown to increase angular inspection coverage and improve sensitivity to small defects in nondestructive evaluation. In this paper, we develop a Fourier-domain approach to full-matrix imaging based on the wavenumber algorithm used in synthetic aperture radar and sonar. The extension to the wavenumber algorithm for full-matrix data is described and the performance of the new algorithm compared with the TFM, which we use as a representative benchmark for the time-domain algorithms. The wavenumber algorithm provides a mathematically rigorous solution to the inverse problem for the assumed forward wave propagation model, whereas the TFM employs heuristic delay-and-sum beamforming. Consequently, the wavenumber algorithm has an improved point-spread function and provides better imagery. However, the major advantage of the wavenumber algorithm is its superior computational performance. For large arrays and images, the wavenumber algorithm is several orders of magnitude faster than the TFM. On the other hand, the key advantage of the TFM is its flexibility. The wavenumber algorithm requires a regularly sampled linear array, while the TFM can handle arbitrary imaging geometries. The TFM and the wavenumber algorithm are compared using simulated and experimental data.     

Range migration algorithm for airborne squint mode spotlight SAR imaging

Since the reference signal based on the fixed reference range is used in the range migration algorithm (RMA), the RMA is not available to process an airborne squint-mode spotlight synthetic aperture radar (SAR) data. Thus, the modified reference signal to transform a squint-mode data to a broadside-mode data is introduced on the basis of the coordinate transformation and the extended Taylor approximation. Then, using the principle of the stationary phase, the presented formulation is analysed. Moreover, to compensate curvature errors, the proposed method is extended on the basis of the subarea technique. Finally, the effectiveness of the proposed method is demonstrated by some numerical simulations via a pulsed spotlight SAR simulator     

有限空间内三维声成像的简易算法

文章提出了一个可用于有限空间内三维声成像的简易算法。根据回声测距原理，得到有限空间中底面上所有采样点在三维笛卡儿空间内的坐标(z，y，z)，然后将其转换为计算机屏幕上的像素点的坐标(z，y)，从而绘制出具有真实立体感的图像。实践证明，利用此算法可以很方便地在计算机屏幕上绘制任意旋转的三维图像。     

Reversible back-propagation imaging algorithm for postprocessing of ultrasonic array data

The paper describes a method for processing data from an ultrasonic transducer array. The proposed algorithm is formulated in such a way that it is reversible, i.e., the raw data set can be recovered from the image. This is of practical significance because it allows the raw-data to be spatially filtered using the image to extract, for example, only the raw data associated with a particular scatterer. The method is tested on experimental data obtained from a commercial 64-element, 5.5-MHz array on an aluminum specimen that contains several machined slots and side-drilled holes. The raw transmitter-receiver data corresponding to each scatterer is extracted, and the scattering matrices of different scatterers are reconstructed. This allows the signals from 1-mm-long slot and a 1-mm-diameter hole to be clearly distinguished and the orientation and the size of the slots to be determined.     

分散式自适应主动隔振控制算法研究

针对主动隔振中次级通道耦合会影响传统FXLMS算法稳定性问题,提出一种分散式解耦优化控制算法。主要是更新控制滤波器系数时忽略作动器与非临近传感器间的耦合,将多通道控制系统简化为多个并联的单通道控制系统,能降低算法运算量。但在一定程度上也会降低系统的收敛速度,为此,在辨识矩阵的估计模型中引入了作动器与非临近传感器之间的反馈补偿因子。仿真和试验结果表明,该算法可有效降低运算量,提高收敛速度和控制精度,双频线谱激励控制效果显著,振动衰减分别可达24.5 dB和12.4 dB。