Estimation and identification for 2-D block Kalman filtering

The development of a recursive identification and estimation procedure for two-dimensional block Kalman filtering is discussed. The recursive identification scheme can be used online to update the image model parameters at each iteration based on the local statistics within a block of the observed noisy image. The covariance matrix of the driving noise can also be estimated at each iteration of this algorithm. A recursive procedure for computing the parameters of the higher order models is given. Simulation results are also provided     

A Hybrid Geometric–Statistical Deformable Model for Automated 3-D Segmentation in Brain MRI

We present a novel 3-D deformable model-based approach for accurate, robust, and automated tissue segmentation of brain MRI data of single as well as multiple magnetic resonance sequences. The main contribution of this study is that we employ an edge-based geodesic active contour for the segmentation task by integrating both image edge geometry and voxel statistical homogeneity into a novel hybrid geometric-statistical feature to regularize contour convergence and extract complex anatomical structures. We validate the accuracy of the segmentation results on simulated brain MRI scans of both single T1-weighted and multiple T1/T2/PD-weighted sequences. We also demonstrate the robustness of the proposed method when applied to clinical brain MRI scans. When compared to a current state-of-the-art region-based level-set segmentation formulation, our white matter and gray matter segmentation resulted in significantly higher accuracy levels with a mean improvement in Dice similarity indexes of 8.55% (p<0.0001) and 10.18% (p<0.0001), respectively.     

2-D Direction-of-arrival Estimation of Real-valued Sources

A new method is presented to estimate two-dimensional （2-D） Direction-of-Arrival （DOA） angles of narrowband real-valued signals impinging on a L-shape Arrays（LA）. The basic idea of the proposed method is to increase both the effective aperture size and the number of sensors by employing the conjugate invariance property of real-valued signals. Thus, the proposed method can provide a more precise DOA and detect more signals than the Cross-Correlation Matrix Method （CCMM）. Numerical simulation results are presented to support the theory.     

Maximum Entropy Power Spectrum Estimation for 2-D Multirate Systems

This paper presents maximum entropy power spectrum estimation of a 2-D information signal given that multirate low-resolution observations are available. Since the exact calculation of the 2-D maximum entropy power spectrum is not practical, we propose an efficient method utilizing slices in the 2-D discrete Fourier transform (DFT) domain and the duality in convex programming. We investigate the properties of our solution and provide numerical examples to demonstrate the performance of the new method.     

基于三维递归搜索的多级运动估计视频帧率上转换算法

运动补偿插帧是目前主要的帧率上转换方法。为减小内插帧中的块效应,并降低运算量以满足实时高清视频应用,该文提出了一种基于3维递归搜索(3-D Recursive Search, 3-D RS)的多级块匹配运动估计视频帧率上转换算法。该算法将3-D RS与双向运动估计相结合,首先对序列中相邻帧进行由粗到精的三级运动估计,再利用简化的中值滤波器平滑运动矢量场,最后通过线性插值补偿得到内插帧。实验结果表明,与现有的运动补偿插帧算法相比,该算法内插帧的主、客观质量都有所提高,且算法复杂度低,有很强的实用性。     

A Super-Resolution Framework for 3-D High-Resolution and High-Contrast Imaging Using 2-D Multislice MRI

A novel super-resolution reconstruction (SRR) framework in magnetic resonance imaging (MRI) is proposed. Its purpose is to produce images of both high resolution and high contrast desirable for image-guided minimally invasive brain surgery. The input data are multiple 2-D multislice inversion recovery MRI scans acquired at orientations with regular angular spacing rotated around a common frequency encoding axis. The output is a 3-D volume of isotropic high resolution. The inversion process resembles a localized projection reconstruction problem. Iterative algorithms for reconstruction are based on the projection onto convex sets (POCS) formalism. Results demonstrate resolution enhancement in simulated phantom studies, and ex vivo and in vivo human brain scans, carried out on clinical scanners. A comparison with previously published SRR methods shows favorable characteristics in the proposed approach.     

用均匀中心对称阵二维西ESPRIT方法实现闭环形式二维角估计

本文提出了适用于一类均匀中心对称阵的二维西ESPRIT方法,它是一种闭环形式的高分辨算法,对信号源方位角和仰角估计实现自动配对.在算法最后阶段构造一个矩阵,其第I个特征值的实部和虚部分别与第I个信号源相对X轴和Y轴的方向余波一一对应.该算法除了初始变换和最后矩阵特征分解外,整个过程都采用高效的实值计算.并推广应用于DFT波束空间,可在较小的空间维数上处理,从而减小计算复杂性.最后对算法做了一阶近似渐进性能分析.仿真结果说明了算法是有效的.     

一种高效的MPEG-2视频编码的运动估计方案

本文提出一种高效的ＭＰＥＧ－２视频编码运动估计方案,该方案利用同一宏块不同类型运动向量之间的相关性,分两级搜索,分析表明采用本文所提出的方案,一ＭＰＥＧ－２测试模型５（ＴＭ５）要比,其计算量有大幅度降低,约为ＴＭ５的１７％;而且模拟实验表明该方案与ＴＭ５的ＭＳＥ、ＰＳＮＲ性能接近。由于两级搜索中都是采用全索策略,易于并行实现,因而本文方案为ＭＰＥＧ－２视频编码运动做主的低复杂度实时实现提供了一种途     

非均匀噪声下频率及二维到达角的联合估计

提出一种适用于L型阵列的频率及二维到达角联合估计新算法.算法通过不同子阵的互协方差矩阵构建平行因子模型,应用三线性交替最小二乘算法求解,无需参数配对及多维搜索,可有效抑制非均匀噪声.均方根误差的仿真结果验证了该算法的有效性.     

一种适用于MIMO雷达的低复杂度二维DOA估计方法

 本文提出了一种适用于收、发共阵多发多收(MIMO)雷达的低复杂度二维波达方向(DOA)估计方法.该方法将MIMO雷达的虚拟二维阵列分解为多个构形相同但位置不同的虚拟子阵,通过一种基于预投影的ESPRIT算法得到同一目标二维DOA的多组估计值,极大地降低了运算量.并利用Kalman滤波器对这多组二维DOA估计值进行融合,提高了估计值的精度.同时,利用收、发对偶性对样本数据进行了重排,等效地将样本数加倍,进一步提高了二维DOA估计精度.数值仿真的结果证明了该方法的有效性.     

一种可自动配对的二维波达方向估计算法

针对非相关远场窄带信号,提出了一种基于L阵模型的低复杂度高分辨二维波达方向估计算法。该方法通过利用互相关矩阵以及L阵的几何结构,消除了附加噪声的影响,且对于方位角和俯仰角的求取仅仅需要一维估计,同时该算法只需对一个低维矩阵进行特征值分解,减少了运算负担,该算法利用特征值求取俯仰角,利用相应的特征向量构造出的虚拟阵列响应矩阵求取与俯仰角配对的方位角。仿真进一步证明了算法的有效性,通过仿真还可以看出,该文所提方法在低信噪比、小快拍数和较小角度间距的情况下都具有良好的性能。     

基于约束MUSIC的二维DOA估计

本文首先分析了约束MUSIC算法的原理,然后采用这种方法,研究了均匀圆阵的二维到达波方向估计问题,并推广到平面任意阵的情况.研究结果表明,对于相关信号源的DOA估计,采用约束MUSIC法比MUSIC法具有更好的估计性能.     

Motion Estimation for Video Coding Standards

Motion-compensated estimation is an effective means in reducing the interframe correlation for image sequence coding. Therefore, it is adopted by the international video coding standards, ITU H.261, H.263, ISO MPEG-1 and MPEG-2. This paper provides a comprehensive survey of the motion estimation techniques that are pertinent to video coding standards.There are three popular groups of motion estimation methods: i) block matching methods, ii) differential (gradient) methods, and iii) Fourier methods. However, not all of them are suitable for the block-based motion compensation structure specified by the aforementioned standards. Our focus in this paper is to review those techniques that would fit into the standards. In addition to the basic operations of these techniques, issues discussed are their extensions, their performance limit, their relationships with each other, and the other advantages or disadvantages of these methods. At the end, an example of evaluating block matching algorithms from a system-level VLSI design viewpoint is provided.     

一种改进的UMHexagonS运动估计算法

在分析UMHexagonS运动估计算法的基础上,根据中心偏移特性在起始搜索点预测中加入了原点预测;利用预测运动矢量的运动信息把当前块的运动类型区分为慢速运动、中速运动和快速运动,并采取相应的搜索策略;考虑到常见视频序列水平、垂直方向运动相对剧烈的特性,提出了用13点中菱形模板和8点多层次大菱形模板分别代替正方形模板和多层次六边形模板;在中菱形搜索和大菱形搜索的步骤后均加入提前终止判定,减少了对不重要搜索点的搜索。仿真结果表明,改进后的新算法在保证信噪比和编码码率基本不变的情况下,使得运动估计的时间减少了10%～23%,增强了编码的实时性。     

非圆信号方位、俯仰及初相联合估计

该文利用双平行线阵的阵列结构,提出了用于非圆信号二维方向和初相联合估计的扩展MUSIC(EN-MUSIC)算法。EN-MUSIC算法估计得到的方位角、俯仰角与初相一一对应,自动配对,其可测向信号数大于子阵阵元数,方位及俯仰测角精度与非圆信号二维测向酉ESPRIT(2D-NC-UESPRIT)算法大致相当,优于波达方向矩阵法(DOAM)。     

运动估计块匹配算法的分析研究

在对目前运动估计快速块匹配算法研究的基础上，描述了运动估计的基本原理；揭示了提高运动估计效率的关键技术，并对相关的算法进行了分析和比较；提出了运动估计算法今后的研究方向。     

用于运动估计的最小化MSE滤波器设计

根据估计量的统计特性,提出了一种适用于低信噪比条件下运动估计的最小化MSE(均方误差)滤波器多尺度运动估计算法.首先,根据Cramer-Rao下界建立一个包含估计量噪声项的MSE惩罚函数.然后,最小化MSE惩罚函数设计一种用于低信噪比条件下运动估计的优化滤波器.该优化滤波器与多尺度方法相结合,使其对低信噪比条件下运动估计的精度得到了进一步提高.实验模拟表明,该方法在估计2个像素附近的噪声图像运动时,估计偏差小于0.008个像素.与传统方法相比,本文方法对低信噪比条件下的运动估计具有更高的估计精度.     

一种用于运动估值的预测搜索算法

本文提出了一种运动估值算法一预测搜索算法（PSA）。该算法由于利用了运动矢量的空间、时间相关性，可以明显减小搜索范围，提高搜索效率，并能给出正确的运动矢量。文中还对预测搜索算法和全搜索算法（FSM）进行了比较。     

Selective Disparity Estimation and Variable Size Motion Estimation Based on Motion Homogeneity for Multi-View Coding

Multi-view video coding (MVC) is an ongoing standard in which variable size disparity estimation (DE) and motion estimation (ME) are both employed to select the best coding mode for each macroblock (MB). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs it from practical use. In this paper, a fast DE and ME algorithm based on motion homogeneity is proposed to reduce MVC computational complexity. The basic idea of the method is to utilize the spatial property of motion field in prediction where DE and variable size ME are needed, and only in these regions DE and variable size ME are enabled. The motion field is generated by the corresponding motion vectors (MVs) in spatial window. Simulation results show that the proposed algorithm can save 63% average computational complexity, with negligible loss of coding efficiency.      

二维子阵级相控阵空间谱估计方法

目前已提出的空间谱估计方法绝大多数需要已知所有阵元的数字化输出信号,即为基于阵元级的方法.我们对应用于相控阵雷达的二维子阵级空间谱估计方法进行了研究.采用简化的阵列流形,只需精确地确定子阵相位中心与增益,大大降低了对相控阵的校正成本与代价.但其有效的方向估计范围只在子阵的3dB波束宽度内,然而与波束扫描相结合可实现任意空间范围内的方向估计.通过引入加权网络对子阵输出进行后处理,提高了阵列处理的灵活性;构造了基于理想子阵方向图的简化阵列流形,克服了直接简化阵列流形方法的测向范围无法调整的局限性,并能更好地抑制旁瓣源.仿真结果证实了所提出方法的有效性.