GRAY

卡尔曼滤波是一种数据处理方法，它是一种线性最小方差无偏估计准则，基于系统 状态估计和当前观测，通过引入状态空间而获得的新的状态估计.本篇论文陈述了卡尔曼滤 波的基本思路和算法；并通过仿真，显示卡尔曼滤波的功能，以及如何用它来跟踪方向确定、速度恒定的飞行器。 (Kalman filter is a data processing method, which is a linear minimum variance unbiased estimation criteria, based on system state estimation and the current observations, obtained by introducing the state space of the new state estimate of the Kalman filter thesis statement the basic ideas and algorithms and through simulation, shows Kalman filtering functions, and how to use it to keep track of the direction determined constant speed aircraft.)

图像处理缩放，大小随意改变，平滑处理，基于vb6.0设计(Zoom image processing, size change, smooth deal, based on the design VB6.0)

VC++,DirectX,运动图像检测,运动轨迹跟踪(VC++, DirectX movement trajectory tracking image detection)

halcon图像处理软件用来检检测图像的圆状物体。可直接使用。 (halcon image processing software is used to check the oblong object detection image. Can be used directly.)

本程序实现位图的读写，均衡化，滤波，LBP，LTP特征提取以及基于LBP，LTP和卡方距离，最近邻分类的人脸识别，批量给图片改名等功能(The program can read and write a bitmap, equalization, filtering, LBP, LTP feature extraction and nearest neighbor classifier for face recognition based on LBP, LTP and chi-square distance, rename picture and some other functions.)

运用基于密度的聚类算法实现了超像素的分割(The segmentation of super pixels is realized by using the clustering algorithm based on density)

使用KINECT获取深度图像的源码，在vs平台下使用C++编写。(Use KINECT obtain depth image source, written using C++ in vs internet.)

基于扫描地形图的几何纠正算法研究。主要讲解了关于倾斜的数字图像的处理问题。(Scanned topographic maps based on the geometric correction algorithm. Mainly on the inclination to explain the deal with the issue of digital images.)

基于ART算法的CT图像重建 刚找到的，不知能不能用(CT image reconstruction based on ART algorithm)

针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )