ImageZoom

包括基于SIFTGPU的sift特征提取，sift匹配，基于ransac误匹配点剔除等(SIFTGPU based sift feature extraction, sift matching, mismatching points based ransac removed, etc.)

用C语言实现最优化算法中的黄金分割法！！(optimization algorithm using c)

数字散斑相关程序，能够计算2副图片的位移，简单的例子，对初学者也许有用。(Digital speckle correlation program can calculate the displacement of two images, a simple example, may be useful for beginners.)

pca-sift算法的实现，采用vc2008开发环境，进行开发，独立运行(pca-sift algorithm, using vc2008 development environment to develop, operate independently)

VisualC++数字图像处理技术详解第2版-光盘 第九章(VisualC++ digital image processing technology Detailed Version 2- CD Chapter IX)

说明：  基于opencv的小面积区域的去除.可以去除面积小于指定面积的无兴趣区域.(Opencv-based small area of the region to remove. Can remove an area of less than the specified area is not interested in the region.)

图像的纹理分析应用实例,主要可用于模式识别当中(image texture analysis application, which can be used for pattern recognition)

DCT 数字水印 VC源代码 DCT 数字水印 VC源代码(DCT digital watermarking VC source code DCT digital watermarking VC source code)

模式识别中相似度-豪斯多夫距离源码,可用于对比算法相似度，也可直接作为函数调用(Hausdorff distance for pattern recognition similarity calculating)

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. )