Performance evaluation of 2-D adaptive prediction filters fordetection of small objects in image data

This work studies the performance of dimensional least mean square (TDLMS) adaptive filters as prewhitening filters for the detection of small objects in image data. The object of interest is assumed to have a very small spatial spread and is obscured by correlated clutter of much larger spatial extent. The correlated clutter is predicted and subtracted from the input signal, leaving components of the spatially small signal in the residual output. The receiver operating characteristics of a detection system augmented by a TDLMS prewhitening filter are plotted using Monte-Carlo techniques. It is shown that such a detector has better operating characteristics than a conventional matched filter in the presence of correlated clutter. For very low signal-to-background ratios, TDLMS-based detection systems show a considerable reduction in the number of false alarms. The output energy in both the residual and prediction channels of such filters is shown to be dependent on the correlation length of the various components in the input signal. False alarm reduction and detection gains obtained by using this detection scheme on thermal infrared sensor data with known object positions is presented.     

A 2-D recursive inverse adaptive algorithm

In this paper, a 2-D form of the recently proposed recursive inverse (RI) adaptive algorithm is introduced. The filter coefficients can be updated along both the horizontal and vertical directions on a 2-D plane. The proposed approach uses a variable step size and avoids the use of the inverse autocorrelation matrix in the coefficient update equation, which leads to an improved and more stable performance. Performance of the 2-D RI algorithm is compared to that of the 2-D RLS algorithm in an image deconvolution and an adaptive line enhancer problem settings. The simulation results show that the proposed 2-D RI algorithm leads to an improved performance compared to that of the 2-D RLS algorithm.     

Further improved 2-D lattice filter structure employing missing reflection coefficients

A new lattice filter structure to model two-dimensional (2-D) autoregressive (AR) fields is proposed. The proposed structure utilizes and extracts the information contained in the backward prediction error fields and their delayed versions. The main idea is to use two sets of reflection coefficients corresponding to two quadrant filters and to increase the number of reflection coefficients with the order of the lattice filter. Increasing the number of reflection coefficients at each stage produces a sufficient number of independent parameters to model AR fields up to order three, which is an improvement over the existing 2-D lattice filter structures. The improvement is confirmed by computer simulations. In addition, a relationship between the reflection coefficients and the AR coefficients is derived. It is also shown that the entropy contained in the backward prediction error field vector of the proposed structure is closer to the input entropy when compared to those contained in existing 2-D lattice filters.     

An improved algorithm for 2-D translational motion artifact correction

The quality of magnetic resonance imaging systems has improved to the point that motion is a major limitation in many examinations. Translational motion in the imaging plane causes the phase of the data to be corrupted. An algorithm using computer post-processing is proposed to correct the phase of the data, and hence remove the artifact. This algorithm has superior convergence properties to an earlier algorithm, which is achieved by incorporating additional prior information specific to the situation. The algorithm is verified using a Shepp and Logan phantom with simulated motion in the imaging plane. It is shown that the algorithm can correct both periodic and random motion, and that the algorithm is not significantly degraded when noise is present.     

海杂波背景下利用DWT提高MTD性能的仿真分析

针对利用传统的窄带滤波器组实现海杂波背景下动目标检测（MTD）时,副瓣电平往往过高这一问题,讨论了离散小波变换（DWT）在MTD中的应用。在瑞利型海杂波背景下,通过对MTD所得到的结果进行小波变换,可以达到提高雷达系统处理增益的同时,降低系统输出的副瓣电平。最后,分别利用Haar小波和db2小波进行了仿真实验,结果证明该方法可以有效地提高MTD性能。     

Analysis of the adaptive matched filter algorithm for cases withmismatched clutter statistics

In the majority of adaptive radar detection algorithms, the covariance matrix for the clutter plus noise is estimated using samples taken from range cells surrounding the test cell. In a nonhomogeneous environment, this can lead to a mismatch between the mean of the estimated covariance matrix and the true covariance matrix for the test cell. Closed-form expressions are provided, which give the performance for such cases when the popular adaptive matched filter algorithm is used. The expressions are exact in some cases and provide useful approximations in others. To simplify the analysis, the samples from the surrounding range cells are assumed to be independent and identically distributed (i.i.d.), and these samples are assumed to be independent from the sample taken from the test cell. The performance depends on a small number of important parameters. These parameters describe which types of mismatches are important and which are not. Numerical examples are provided to illustrate how performance varies with each of the important parameters. Monte Carlo simulations are included that closely match the predictions of our equations. An airborne radar example is provided that demonstrates that covariance matrix mismatch can have a significant effect on performance in some practical cases     

二维分母可分离状态空间滤波器的PSO实现

基于Deb在文献[1]中所提出的思想和竞争型神经网络[2]的特点,提出了PSO的一种改进算法。并利用该算法对二维分母可分离状态空间滤波器进行仿真,结果表明所改进的算法不仅能有效地提高SSE的收敛速度,而且使收敛过程更趋平滑。     

基于改进麻雀算法的最大2维熵分割方法

为了提高最大2维熵分割的性能,提出了基于改进麻雀算法的最大2维熵分割方法,可减小运算量并且缩短计算时间.首先,融合反向学习策略和自适应t分布变异,引入精英粒子,以扩大算法搜索范围,增加算法后期局部搜索能力;其次,使用萤火虫机制,对最优解进行扰动变异,进一步增加种群多样性;最后,采用提出的改进麻雀算法寻找图像最大2维熵,...     

基于改进遗传算法的最大2维熵图像分割

为了解决传统最大2维熵分割算法计算量大、耗时较多等缺陷，提出一种基于改进遗传算法的最大2维熵图像分割法。通过对遗传算法变异操作方式进行改进，提高遗传算法寻找最大2维熵分割阈值的速度，加速分割算法对图像的分割，并进行了仿真实验验证。结果表明，改进模型的运行时间被压缩到了0.95s，远远低于传统的最大2维熵分割法。改进的分割方法实现了分割效率的提高，同时也保证了图像的分割精度。     

强起伏云背景下的小目标图像预处理算法

强起伏云背景下的小目标分割是图像处理中的重点和难点之一.本文将高通滤波和数学形态学图像处理算法相结合,提出一种新的预处理方法.首先,利用高通滤波器作为背景抑制滤波器,消除强起伏云背景对图像分割的影响;其次,利用阈值算法将背景抑制后的图像转化为二值图像;最后,应用形态学方法消除噪声得到最终的小目标分割结果.仿真试验表明,该算法具有较好的预处理效果.     

基于改进鲸鱼优化算法的最大2维熵图像分割

为了避免原鲸鱼优化算法早熟收敛、易陷入局部最优等缺陷,首先在原鲸鱼优化算法初始化过程中采用了猫映射产生混沌序列结合反向解方法取代随机产生初始种群;其次在位置更新机制上采用了疯狂算子和黄金正弦算法的方法;最后将改进鲸鱼优化算法用于寻求图像2维最大熵来确定图像分割最佳阈值的选取.对10个经典基准函数进行了试验仿真验证,得到...     

改进的LMS自适应噪声对消算法的应用

针对工业噪声的特点,将自适应对消算法应用到工业噪声的处理中。根据传统最小均方(Least Mean Square,LMS)自适应算法的缺点,文中通过构造合适的步长因子,引入参数使得算法在提高收敛速度的同时保证较小的稳态误差。放宽算法的约束性条件,以提高步长调整的精度。实验验证,提出的算法与其他算法相比,具有更快的收敛速度、更小的稳态误差以及优良的抗干扰性能。     

一种改进型自适应A-MAC算法分析与仿真

无线传感器网络的MAC协议可以利用监听/睡眠周期节约能源。对监听/睡眠周期和网络性能的关系进行了分析,研究了自适应的MAC协议及改进算法,通过动态调整节点唤醒的周期和相位来适应网络的动态变化。仿真表明改进后的协议可以减少时延,提高吞吐量和能源效率。     

一种基于格型正交化的二阶Volterra自适应滤波算法

针对 Volterra 自适应滤波器输入信号相关性或附加的非线性畸变的增强使自适应滤波器性能下降的问题,本文提出基于格型正交化的二阶 Volterra 自适应滤波算法.先对输入信号进行格型预处理,得到互相正交的后向预测误差信号;然后将其作为自适应滤波器的输入,从而大大降低了一次项、平方项和交叉乘积项信号各项之间的耦合,改善了自适应算法的收敛性能.有源噪声对消的仿真结果表明,在输入噪声强相关和附加较强非线性畸变时本算法仍具有较好的消噪性能.     

Saddle-point based separation of touched objects in 2-D image

In many image analysis and processing problems, discriminating the size and shape of each individual object in an aggregate pile projected in an image is an important practice. It is relatively easy to distinguish these features among the objects already separated from each other. The problems will be undoubtedly more complex and of greater challenge if the objects are touched or/and overlapped. This letter presents an algorithm that can be used to separate the touches and overlaps existing in the objects within a 2-D image, The approach is first to convert the gray-scale image to its corresponding binary one and then to the 3-D topographic one using the erosion operations. A template （or mask） is engineered to search the topographic surface for the saddle point, from which the segmenting orientation is determined followed by the desired separating operation, The algorithm is tested on a real image and the running result is adequately satisfying and encouraging.     

一种PN码自适应捕获门限的改进算法

文献[1]提出了一种用于直扩系统的PN码自适应门限算法。但该文献也指出,此算法对门限总数十分敏感。当门限总数设置不当时,系统的平均捕获时间将显著增加。这限制了该算法在实际中的应用。本文就此提出了改进,给出了算法及电路框图。仿真结果表明,与原方案相比,改进算法改善了对门限总数的敏感性,降低了PN码平均捕获时间。     

GPS空时抗干扰中一种改进的MWF算法的应用

在GPS接收机的抗干扰抑制中,较单纯时域、频域或空域滤波方法,空时联合处理利用了更多的接收数据信息,因而可以获得更好的干扰抑制性能。针对空时处理方法计算量大的缺陷,文中通过降维处理思想的分析,给出了一种对MWF的前向递推过程进行简化的方法,以此来降低运算量,缩短运算所需的时间,并将这种方法与一般方法进行降秩性能和抗干扰...     

2-D FFT algorithm by matrix factorization in a 2-D space

A new 2-D FFT algorithm is described. This algorithm applies a 2-D matrix factorization technique in a 2-D space and offers a way to do 2-D FFT in both dimensions simultaneously. The computation is greatly reduced compared to traditional algorithms. This will improve the realization of a 2-D FFT on any kind of computer. However its good parallelism will especially benefit an implementation on a computer with hypercube architecture. A good arrangement of parallel processors will save a great deal of running time. Furthermore this algorithm can be extended toM-D cases forM>2.Supported by NSF Grant CCR-8813493.Supported by Grants DMS-8607687, DMS-8722402, and DMS9002019.     

三维大尺寸介质目标散射问题的总场边界PSTD技术

传统的伪谱时域差分(PSTD)方法中不存在硬连接边界条件,基于Gao 等人的思想,在PSTD计算区域内设置8～10个网格层的连接区.通过引入加权窗函数,使得整个计算区域被有效地划分为总场区、连接区和散射场区.总场边界PSTD技术在成功地把入射波引入到PSTD计算区域内的同时,更便于复杂目标离散建模.以时域高斯脉冲为宽频带平面入射波,通过数值算例,验证了总场边界PSTD技术应用于三维大尺寸介质目标散射问题的有效性和实用性.     

Matrix analysis of 2-D microresonator lattice optical filters

We present a transfer matrix analysis of a two-dimensional (2-D) filter to study its frequency response functions. The (M/spl times/N) array consists of N independent columns of microring resonators side-coupled to two channel bus waveguides, with equal spacing between columns and each column consisting of M coupled resonators. We show that such a general 2-D lattice network of lossless and symmetric resonators can approximate an ideal bandpass filter characterized by a flat-top box-like amplitude response without out-of-band sidelobes, and a linear phase response. The bandwidth is determined by the coupling factor between resonators. The 2-D periodic structure exhibits nonoverlapping photonic bandgaps arising from the complementary transmission properties of the row and column arrays. The row array behaves as a distributed feedback grating giving rise to narrow bandgaps corresponding to the flat reflection passbands of the filter with out-of-band sidelobes. The column array, on the other hand, acts as a high-order coupled-cavities filter with broad bandgaps that overlap with the sidelobe regions, thereby effectively suppressing the sidelobes. The phase response is linear except near the band edges, where enhanced group delay limits the usable bandwidth of the filter to about 80%. The minimum size of the array required is about 3/spl times/10, but is ultimately limited by waveguide loss.