基于开关3-D中值滤波的视频序列去噪算法

为提高含噪视频序列的质量和效果,提出一种基于开关噪声检测与三维中值滤波相结合的开关3-D中值滤波算法。该算法通过判断视频序列的每一个像素点,对噪声点用3-D中值滤波处理,再对其进行二次判断,如果判为噪声点,则采用变型3-D中值滤波处理,直到去除所有噪声点为止。仿真实验表明,该算法对“雪花”噪声有较好的滤波效果,当处理加入25%的“雪花”噪声时,3-D开关中值滤波比三维中值滤波的信噪比平均提高了10 dB左右。     

求解独立任务调度的离散粒子群优化算法

针对独立任务调度问题,提出一种改进的离散粒子群算法,采用基于任务的编码方式,对粒子的位置和速度更新方法进行重新定义。为防止粒子群算法的早熟收敛,给出利用模拟退火算法的局部搜索能力在最优解附近进行精细搜索,以改善解的质量。仿真结果表明,与遗传算法和基本粒子群算法相比,该混合算法具有较好的优化性能。     

基于粒子滤波器的人体目标跟踪

提出一种非常有效且具有良好鲁棒性的人体目标跟踪算法。由于传统的卡尔曼滤波不能很好地解决非线性、非高斯问题的跟踪,为此提出了一种新型的粒子滤波器跟踪算法。该算法采用加权的粒子集模型表示状态的分布,用迭代运算跟踪状态的变化,从而有效地解决了数据处理的量大和模型出现高维的问题。实验结果证明,该算法对固定摄像机单一背景下人体目标跟踪是快速且有效的。该算法可广泛应用于航空器位置的跟踪、噪声环境通信信号的估计、人体或车辆的跟踪。     

基于粗糙集理论的图像平滑算法研究

基于粗糙集理论,针对高斯噪声和脉冲噪声,分别采用高斯模板和中值滤波技术,提出了图像平滑算法.这两种算法在去噪的同时,都能够很好地保持图像细节,并且简单易行、处理速度快、使用范围广.通过实验,该算法对灰度图像和彩色图像的处理效果较之传统的处理方法,质量上有较大的提高.     

平均曲率运动的三种实现方案的比较研究

讨论了曲率运动演化方程的三种数值方案:离散中值滤波方案、显式水平集方案和半隐式水平集方案的原理与算法,并对它们的效率、精度以及旋转不变性等性能进行了对比实验研究.结果表明,半隐式加性算子分裂(AOS)算法相对于另两种方案性能上明显占优.     

Real-time reliability prediction for dynamic systems with both deteriorating and unreliable components

As an important technology for predictive maintenance, failure prognosis has attracted more and more attentions in recent years. Real-time reliability prediction is one effective solution to failure prognosis. Considering a dynamic system that is composed of normal, deteriorating and unreliable components, this paper proposes an integrated approach to perform real-time reliability prediction for such a class of systems. For a deteriorating component, the degradation is modeled by a time-varying fault process which is a linear or approximately linear function of time. The behavior of an unreliable component is described by a random variable which has two possible values corresponding to the operating and malfunction conditions of this component. The whole proposed approach contains three algorithms. A modified interacting multiple model particle filter is adopted to estimate the dynamic system’s state variables and the unmeasurable time-varying fault. An exponential smoothing algorithm named the Holt’s method is used to predict the fault process. In the end, the system’s reliability is predicted in real time by use of the Monte Carlo strategy. The proposed approach can effectively predict the impending failure of a dynamic system, which is verified by computer simulations based on a three-vessel water tank system.     

Statistical learning makes the hybridization of particle swarm and differential evolution more efficient—A novel hybrid optimizer

This brief paper reports a hybrid algorithm we developed recently to solve the global optimization problems of multimodal functions, by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). In the hybrid denoted by DEPSO, each individual in one generation chooses its evolution method, DE or PSO, in a statistical learning way. The choice depends on the relative success ratio of the two methods in a previous learning period. The proposed DEPSO is compared with its PSO and DE parents, two advanced DE variants one of which is suggested by the originators of DE, two advanced PSO variants one of which is acknowledged as a recent standard by PSO community, and also a previous DEPSO. Benchmark tests demonstrate that the DEPSO is more competent for the global optimization of multimodal functions due to its high optimization quality. Supported by the National Natural Science Foundation of China (Grant No. 60374069), and the Foundation of the Key Laboratory of Complex Systems and Intelligent Science, Institute of Automation, Chinese Academy of Sciences (Grant No. 20060104)     

基于模糊理论的椒盐噪声滤波算法

针对图像中的椒盐噪声,基于模糊理论设计了一种滤波算法。首先结合椒盐噪声特点,借助窗口进行噪声检测,其次设计了自适应的方法消除噪声,最后采用图像进行实验,定性和定量分析结果表明该方法对于椒盐噪声的消除可行有效。     

后期模拟制作相机镜头背景模糊效果

在摄影实践中,虚化背景是突出主体的常用手段。但是由于消费级DC镜头的实际焦距都很短,因此实现浅景深而虚化背景的难度较大。如果我们希望用消费级DC也能达到虚化背景突出主体的效果,那么,Photoshop后期处理可以派上用场。     

基于混沌粒子群算法和Hopfield网络求解TSP问题

针对Hopfield网络求解TSP问题经常出现局部最优解,该文将混沌粒子群算法(PSO)与之结合,提出一种基于混沌粒子群的Hopfield神经网络方法。通过实验将其与文献[5,8]以及"PSO+HNN"策略比较,验证了该文算法不仅能够以更大概率收敛到全局最优,而且耗时更少。