位相编码振幅调制联合变换相关器的设计

采用位相编码技术减小了经典联合变换相关器中的直流分量 ,及多目标输入时各目标图像之间的互相关项 ,并且同时消除了参考图像和各目标图像之间的共轭相关项。通过对联合功率谱进行振幅调制 ,缩小了相关峰的宽度 ,锐化了相关峰 ,增强了识别能力。最后给出了计算机模拟结果。     

飞秒脉冲干涉自相关修正光谱的啁啾特性

为了测量飞秒激光脉冲啁啾,采用了一种对干涉自相关光谱作频谱修正的简单方法,得到干涉自相关修正光谱.利用该修正光谱对啁啾有很高灵敏度的特性,对高斯型强度分布的线性啁啾、平方啁啾脉冲进行了理论分析和实验验证,取得了修正光谱的下包络峰的高度与啁啾量对应关系、下包络峰的个数与啁啾次数对应关系.结果表明,根据干涉自相关修正光谱下包络的峰值,可估定啁啾的量值,根据干涉自相关修正光谱下包络峰的个数可以判断脉冲啁啾的次数.这一结果对精确地测量飞秒激光脉冲的微小啁啾量是有帮助的.     

用干涉自相关包络宽度测量超短激光脉冲啁啾

为了测量超短激光脉冲啁啾值,提出了一种用2次干涉自相关包络宽度测量啁啾值的简单方法。利用2次干涉自相关包络宽度对啁啾有很高的灵敏度、含有不同啁啾量的超短激光脉冲有不同的包络宽度的特性,通过对高斯型强度分布的线性、平方及立方啁啾的干涉自相关包络函数进行了理论分析,得到包络宽度与啁啾量值之间的对应关系。采用干涉自相关2次谐波检测系统对加浓染料激光器输出的含有啁啾的脉冲进行测量,其干涉自相关包络宽度为1.15,被测超短激光脉冲啁啾为1.0。结果表明,根据含有啁啾的干涉自相关曲线两翼的特征,可判断啁啾阶数,再根据包络宽度与啁啾值的对应关系,可估定啁啾量值;用干涉自相关包络宽度能容易地测量超短激光脉冲的啁啾量值。     

单模光纤中光脉冲啁啾的分析

论述了啁啾光脉冲在单模光纤中传输时啁啾和脉宽的变化，以及此变化与相应的频谱相位变化的关系．详细分析了啁啾变化的规律，并讨论了其物理图像及该规律在光纤通信中的应用．实验中所获得的脉宽变化与理论计算相符。     

使用功率谱相减的实时联合变换相关器作多目标检测

提出一种使用功率谱相减的实时联合变换相关器作多目标检测。使用这种方法，输入面有两套联合图像。在第二套联合图像中，参考图像是对比度反转的。使用衍射光栅对这两套联合功率谱作相减处理，这种方法可大大抑制输出面的直流项及不想要的伪相关峰，增强相关峰的强度、锐度和峰噪比，提高抗噪声干扰的能力，从而提高对多目标检测的准确度。给出对具有灰度级的多目标输入景物的计算机模拟结果和光学实验结果。实验结果证实了该系统设计及性能分析的正确性。     

脉冲啁啾对高次谐波谱影响的理论研究

采用单电子近似和软核势模型 ,通过数值求解一维含时薛定谔方程的方法 ,研究了当脉冲分别带有正、负啁啾的情况下所产生的高次谐波谱的变化。结果表明 ,对于正啁啾脉冲 ,其高次谐波谱将出现分裂 ,而对于负啁啾 ,高次谐波谱呈现展宽的趋势。同时发现 ,在激光脉冲带有很大的啁啾的情况下 ,无论是正啁啾还是负啁啾 ,都会使谐波峰分裂成多个更加细小的谱峰     

啁啾相移光纤光栅的反射谱特性

相移光纤光栅作为透射型滤波器件降低了使用成本,在光通信和传感领域有着较高的应用价值.将传输矩阵法与谐振理论相结合,详细分析了相移量、相移点位置对啁啾相移光栅反射谱特性的影响,数值模拟和实验结果表明,啁啾相移光栅与均匀相移光栅不同,当位于啁啾光栅中点的相移调制量偏离π/2时,透射峰在偏离光栅反射谱中心的同时深度逐渐减小;当相移点在光栅上的位置发生变化时,透射峰位置也随之改变,但深度基本保持不变.利用啁啾光栅的这种特性,可形成具有多个透射峰的多点相移光栅.     

宽带FBG与自相关算法提高CCD解调精度的研究

为提高光纤光栅解调算法的精度,设计了3 dB带宽在1~3 nm之间的宽带布拉格光栅与自相关算法解调系统,使用线阵CCD检测光谱,进行波长寻峰分析与实验验证。线阵CCD离散像素点之间波长间距固定,宽带布拉格光栅可得到更多有效像素数据点;自相关算法只考虑传感测量时光谱的偏移程度,可抵消背景噪声,消除光栅刻写或封装过程中操作不当引起光谱异常的影响,从而提高光栅中心波长解调精度。温度测量结果表明,使用自相关算法解调啁啾光栅与宽带光栅,误差较高斯算法分别减少54.05%和40.87%,此算法可以使啁啾光栅达到正常光栅的解调精度。并且,使用宽带光栅的解调误差仅为啁啾光栅的50%。     

高斯脉冲在光纤中传输的光纤光栅色散补偿研究

高斯脉冲在光纤中传输一段距离后，啁啾系数和脉冲宽度均要发生变化，不同啁啾系数和脉冲宽度的高斯脉冲经过啁啾光纤光栅反射后的脉宽压缩特性也不同。本文介绍了啁啾高斯脉冲在光纤中的传输特性以及啁啾高斯脉冲经啁啾光纤光栅反射后的传输特性。理论分析和实验均表明，使用啁啾光纤光栅实现长距离色散补偿时，最佳色散补偿长度与光栅位置有关。     

超短啁啾高斯脉冲叠加光束的空间异常特性分析

以ICF系统应用为背景，建立了四束超短啁啾高斯脉冲远场能量叠加分析模型，分别对单束及多束超短啁啾高斯脉冲的空间异常特性进行了数值模拟和分析。结果表明:脉宽是影响超短啁啾高斯脉冲叠加光束产生空间异常现象的主要因素。在利用指数函数复振幅包络的解析式进行分析时，使用脉宽小于1个光振荡周期的超短啁啾高斯脉冲进行叠加应控制参数在合理的范围内，r1w0时可有效避免空间异常现象。     

Intra frame compression and video restoration based on conditional markov processes theory

Digital images and video have significant statistical redundancy due to high intra and inter-frame correlation. Modeling images and video using two-dimensional Markov processes with discrete states maximizes the use of images and video redundancy while processing. Intra-frame compression algorithm proposed below allows 2–3 times increase in processing speed for comparable compression ratios. Nonlinear filtering algorithm of video (distorted during transmission on a radio channel in terms of interference) allows effective video restoring even for negative signal/noise ratio unlike the known methods. A distinctive feature of this algorithm is ease of implementation with minimal computing resources.     

Interpolation Artifacts in Sub-Pixel Image Registration

We consider the problem of registering (aligning) two images to sub-pixel accuracy by optimization of objective functions constructed from the images' intensity values. We show that some widely used interpolation methods can introduce multiple local optima in the energy of the interpolated image which, if not counter-balanced by other terms, can cause local optima in registration objective functions including the sum of squared differences, cross correlation, and mutual information. We discuss different solutions to address the problem based on high degree B-spline interpolation, low pass filtering the images, and stochastic integration. Numerical examples using synthetic and real signals and images are shown.     

一种高分辨率3维图像的自适应降噪算法

为了获得高保真3维图像,采用了一种针对高分辨率3维图像的自适应均值降噪算法。首先使用一种由激光器、高分辨率3维相机、直线电机和计算机等设备组成的线激光高精度3维测量实验系统对自然纹理皮革进行测量。然后针对系统测量所得的高分辨率3维自然纹理图像(每英寸点数大于1000),进行了理论分析和实验验证,取得了降噪后的高保真3维图像数据,并与传统的均值滤波、小波变换滤波的降噪效果进行对比。结果表明,该算法能自动选取最优的降噪窗口,有效地去除3维图像的噪声信息,并保留高分辨率图像丰富的边缘、细节信息,最终得到高保真的高分辨率3维自然纹理图像。该实验结果对于高分辨率图像的降噪问题是十分有帮助的。     

Convergence results for the particle PHD filter

Bayesian single-target tracking techniques can be extended to a multiple-target environment by viewing the multiple-target state as a random finite set, but evaluating the multiple-target posterior distribution is currently computationally intractable for real-time applications. A practical alternative to the optimal Bayes multitarget filter is the probability hypothesis density (PHD) filter, which propagates the first-order moment of the multitarget posterior instead of the posterior distribution itself. It has been shown that the PHD is the best-fit approximation of the multitarget posterior in an information-theoretic sense. The method avoids the need for explicit data association, as the target states are viewed as a single global target state, and the identities of the targets are not part of the tracking framework. Sequential Monte Carlo approximations of the PHD using particle filter techniques have been implemented, showing the potential of this technique for real-time tracking applications. This paper presents mathematical proofs of convergence for the particle filtering algorithm and gives bounds for the mean-square error.     

红外多目标跟踪算法研究

介绍了红外搜索跟踪系统中多目标跟踪与航迹生成算法，采用极坐标数据进行数据的关联和滤波，采用基于逻辑的最近邻原则并结合目标的红外辐射特性进行航迹关联，实现多目标跟踪起始和终结。     

Adaptive progressive filter to remove impulse noise in highly corrupted color images

In this paper, an adaptive progressive filtering (APF) technique with low computational complexity is proposed for removing impulse noise in highly corrupted color images. Color images that are corrupted with impulse noise are generally filtered by applying a vector-based approach. Vector-based methods tend to cluster the noise and receive a lower noise reduction performance when the noise ratio is high. To improve the performance, in the proposed technique, a new reliable estimation of impulse noise intensity and noise type is made initially, and then a progressive restoration mechanism is devised, using multi-pass non-linear operations with selected processing windows adapted to the estimation. The effect of impulse detection based on geometric characteristics and features of the corrupt pixel/pixel regions and the exact estimation of impulse noise intensity and type are used in the APF to efficiently support the progressive filtering mechanism. Through experiments conducted using a range of color images, the proposed filtering technique has demonstrated superior performance to that of well-known benchmark techniques, in terms of standard objective measurements, visual image quality, and the computational complexity.     

基于双马尔科夫链的势概率假设密度滤波

针对已有的基于双马尔科夫链(PMC)模型的势概率假设密度(PMC-CPHD)滤波算法无法实现的问题,将PMC-CPHD算法改进为多项式形式以便于算法的实现,并给出了改进算法的高斯混合(GM)实现。实验结果表明给出的GM实现能够有效实现多目标跟踪,并且比基于PMC模型的概率假设密度(PMC-PHD)算法的GM实现提高了目标个数估计的稳定性。     

Extensions of the SMC-PHD filters for jump Markov systems

The probability hypothesis density (PHD) filter is a promising algorithm for multitarget tracking, which can be extended for jump Markov systems (JMS). Since the existing multiple model sequential Monte Carlo PHD (MM SMC-PHD) filter is not interacting, two extensions of the SMC-PHD filters are developed in this paper. The interacting multiple-model (IMM) SMC-PHD filter approximates the model conditional PHD of target states by particles, and performs the interaction by resampling without any a priori assumption of the noise. The IMM Rao-Blackwellized particle (RBP) PHD filter uses the idea of Rao-Blackwellized to further enhance the performance of target state estimation for JMS with mixed linear/nonlinear state space models. The simulation results show that the proposed algorithms have better performances than the existing MM SMC-PHD filter in terms of state filtering and target number estimation.     

Fast switching based median–mean filter for high density salt and pepper noise removal

This paper proposes a fast switching based median–mean filter for high density salt and pepper noise in images. The extreme minimum value and extreme maximum value of the noisy image are used to identify the noise pixels. In the filtering stage, the corrupted pixel is replaced either by median value or mean value based on the number of noise free pixels in the filtering window. The qualitative and quantitative results show that the proposed filter outperforms the other switching based filters namely ACWMF, PSMF, AMF, DBA and MDBUTMF in terms of noise removal and edge preservation for noise densities varying from 10% to 90%.